Location: San Francisco, CA | New York City, NY
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role:
Anthropic’s Research Tools team builds systems that support our large-scale, distributed finetuning runs and improve the productivity of researchers. As a manager, you’ll support a team of machine learning and distributed systems experts to make these systems and tools highly efficient, support fast iteration on model development and research, and evolve the infrastructure continuously to incorporate new research advances.
Our Research Tooling sits at the intersection of almost every technical group at Anthropic. You’ll work with research teams to incorporate their innovations into our production finetuning pipeline, product teams to help us iterate quickly on customer-oriented model improvements, and infrastructure teams to make sure our training runs and data pipelines are as efficient as possible.
About Anthropic:
Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and society as a whole. Our interdisciplinary team has experience across ML, physics, policy, business, and product.
Responsibilities:
Prioritize the team’s work in collaboration with the technical lead, research teams, and product teams to support fast iteration on research projects and training runs.
Design processes (e.g., postmortem review, incident response, on-call rotations) that help the team operate effectively.
Coach and support your reports to understand and pursue their professional growth.
Run the team’s recruiting efforts efficiently, ensuring we can grow as quickly as we need through a period of rapid growth.
You may be a good fit if you:
Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well.
Are an experienced manager (at least 2 years) and actively enjoy people management.
Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level) to be effective.
Strong candidates may also have:
Experience working with research teams, especially as part of a “research to production” pipeline
Strong people management experience: Coaching, performance evaluation, mentorship, career development
Strong project management skills: Prioritization, communicating across team/org boundaries
Experience recruiting for your team: Predicting staffing needs, designing interview loops, evaluating candidates, and closing them
Deadline to apply:
None. Applications will be reviewed on a rolling basis.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$405,000
—
$850,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: United Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications. You will work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio.
We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments. The ultimate goal is to enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios.
Responsibilities
Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint.
Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across platforms.
Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices. Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions.
Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics. Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems.
Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Must have knowledge of Metal Shading Language (MSL). You should be comfortable writing custom compute shaders from scratch.
Proven experience in low-level kernel optimizations and inference optimization on mobile devices is essential. Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms.
A deep understanding of modern model serving architectures and inference optimization techniques is required. This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios.
Must have strong expertise in writing GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines. Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required.
Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints. You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency.
Distributed Inference Systems: Designing and optimizing high-performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters.
Deep understanding of the math and structure behind Diffusion Models and Vision Transformers
Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc.
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: Bangalore, India
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: Brussels, Belgium
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: Abu Dhabi, United Arab Emirates
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: Amsterdam, Netherlands
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: Barcelona, Spain
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: Sao Paulo, Brazil
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: Dublin, Ireland
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: London, United Kingdom
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: Dubai, United Arab Emirates
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: United Kindom, United Kingdom
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance.
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Experience with PyTorch deep learning frameworks or equivalent frameworks
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.
Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: United Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of the AI model team, you will drive innovation in training and optimizing vision-language models with a focus on real-world deployment. Your work will span the full model development lifecycle - from data curation and training pipeline design to model evaluation and optimization - with the goal of building models that are both highly capable and practical to deploy at scale.
You will work across a wide spectrum of multimodal architectures integrating text and vision, applying state-of-the-art research to improve model quality, efficiency, and domain-specific performance. We expect you to bring a research-driven mindset combined with strong engineering discipline - someone who can identify the right technique for a given problem, implement it rigorously, and measure its impact clearly.
You will work closely with a small, high-caliber team where your contributions will have direct and meaningful impact. If you are passionate about pushing the boundaries of what multimodal AI can achieve in production environments, this is your opportunity.
Responsibilities
Conduct end-to-end research and engineering on vision-language models, covering training, evaluation, and optimization across the full model development lifecycle.
Design and implement post-training pipelines including supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback.
Develop and maintain high-quality multimodal datasets, including data curation, filtering, and balancing for domain-specific tasks.
Drive model efficiency and deployability, adapting models for resource-constrained environments using compression and optimization techniques.
Design and implement evaluation frameworks and benchmarks to measure model performance, robustness, and real-world task success.
Build and scale training workflows across distributed GPU infrastructure.
Identify and resolve bottlenecks in training pipelines to achieve state-of-the-art model quality on target benchmarks.
Contribute to and leverage open-source ecosystems including models, datasets, and tooling to accelerate development.
Stay current with the latest research in multimodal learning and vision-language systems, translating relevant findings into practical improvements.
Publish research findings in top-tier AI conferences and journals where applicable.
Degree in Computer Science, Machine Learning, or a related field; MS/PhD preferred.
Strong experience with multimodal post-training workflows including supervised fine-tuning, knowledge distillation, and reinforcement learning from feedback.
Hands-on experience with parameter-efficient fine-tuning and distributed training frameworks.
Demonstrated ability to build and improve vision-language models with measurable results on standard benchmarks or real-world tasks.
Experience adapting models for resource-constrained environments.
Proven open-source contributions in multimodal AI on GitHub or HuggingFace.
Publications at top AI conferences (NeurIPS, ICML, ICLR, CVPR, ECCV etc.)
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: United Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of the AI model team, you will drive innovation in multi-modal reinforcement learning to advance next-generation intelligent systems. Your work will focus on optimizing decision-making and adaptive behavior across integrated data modalities such as text, images and audio to deliver enhanced intelligence, robust performance, and domain-specific capabilities for real-world challenges. You will develop and scale reinforcement learning techniques within complex multi-modal architectures, including diffusion-based generative models and autoregressive models for multimodal understanding, as well as resource-efficient models designed for constrained hardware environments. This includes conducting research on reinforcement learning algorithms for multimodal models, spanning diffusion models for image autoregressive models for multimodal reasoning, and unified multimodal frameworks.
You are expected to have deep expertise in designing multi-modal reinforcement learning systems and a strong background in advanced model architectures, with a hands-on, research-driven approach to building and deploying novel algorithms and training frameworks. You will design and develop RL infrastructure and reward modeling strategies to enable efficient large-scale training, improve training stability, and mitigate reward hacking and related failure modes. Your responsibilities also include curating multi-modal simulation environments and training datasets, improving baseline policy performance across modalities, and identifying and resolving bottlenecks in multi-modal learning and reward optimization. In addition, you will explore next-generation reinforcement learning paradigms that more directly and effectively learn from environment feedback, with the goal of unlocking superior, domain-adapted AI performance in dynamic, real-world environments.
Responsibilities
Conduct research on reinforcement learning algorithms for multimodal models, including diffusion-based approaches for image autoregressive models for multimodal understanding, and unified frameworks that integrate multiple modalities.
Design and build reinforcement learning infrastructure that supports scalable, distributed training across multimodal systems while maintaining efficiency and reliability.
Develop and refine reward modeling strategies that improve training stability, align model behavior with desired outcomes, and mitigate reward hacking and related failure modes.
Create and curate multimodal simulation environments and datasets to support robust training, evaluation, and benchmarking of reinforcement learning systems.
Design and conduct rigorous benchmarking and evaluation protocols to measure model performance, track progress against baselines, and validate improvements across multimodal tasks.
Analyze and optimize policy performance across modalities by identifying bottlenecks in training, credit assignment, and cross-modal alignment.
Investigate and develop next-generation reinforcement learning paradigms that more effectively learn from environment feedback, with the goal of achieving superior state-of-the-art (SOTA) performance.
Publish research findings in top-tier conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV etc.
A Master's degree in Computer Science or a related field is required; a PhD in Machine Learning, NLP, Computer Vision, or a closely related discipline is preferred, along with a strong track record of AI research and publications in top-tier conferences.
Proven experience running large-scale reinforcement learning experiments in multimodal and vision-centric systems, including online RL settings, with demonstrated impact on domain-specific decision-making and measurable improvements in policy performance.
Deep understanding of reinforcement learning algorithms and optimization methods applied to vision and multimodal learning problems, with a focus on improving policy stability, exploration, and sample efficiency in complex, high-dimensional environments involving images, video, and other modalities.
Strong proficiency in PyTorch and deep learning frameworks for vision and multimodal AI, with hands-on experience building end-to-end RL pipelines covering simulation, training, evaluation, and deployment in production-grade systems.
Demonstrated ability to apply empirical research to solve core RL challenges in multimodal and vision tasks, such as sample inefficiency, exploration-exploitation tradeoffs, and training instability, along with experience designing robust evaluation frameworks and iterating on algorithmic improvements to advance agent performance.
Proven track record of research publications in top-tier conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV etc.
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: United Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of the AI model team, you will drive innovation in post-training methodologies, with a special focus on agentic behaviors and tool use. Your work will refine pre-trained models so that they not only deliver enhanced intelligence and domain specific capabilities, but also learn to reason, plan, and autonomously invoke external tools to solve real world, multi step tasks and applications on edge devices (i.e., smartphones).
You will work on a wide spectrum of systems, ranging from streamlined, resource efficient agents that run on limited hardware to complex multi modal architectures integrating text, images, and audio, all optimized for tool augmented decision making.
We expect you to have deep expertise in large language model architectures and substantial experience in post-training for agentic workflows, including tool use fine tuning, function calling, and reinforcement learning from feedback on multi turn interactions. You will adopt a hands-on, research driven approach to developing, testing, and implementing new post-training algorithms that unlock goal directed behavior, self correction, and reliable tool invocation.
Your responsibilities include curating agentic training data (e.g., trajectories of tool use, reasoning chains, environment interactions), strengthening baseline performance, and identifying as well as resolving bottlenecks in post-training for tool augmented agents to achieve SOTA model quality. The goal is to build models that do not just know but also act, use tools, and adapt, pushing the limits of what agentic AI can achieve.
Responsibilities
Conduct end-to-end research and engineering initiatives to advance post-training of agentic and tool-use models to achieve SOTA results.
Drive broad, cross-cutting model improvements, including factuality, instruction adherence, tool/function use, multi-agent coordination, and reasoning calibration.
Design and enhance large-scale post-training systems, including data pipelines, training workflows, evaluation frameworks, and benchmark infrastructure.
Develop rigorous evaluation suites and diagnostic tools to assess model readiness for deployment.
Strengthen feedback loops from real-world product usage, incorporating both explicit and implicit user signals into post-training.
Collaborate with tooling, product, and training teams to improve the usefulness, reliability, and agentic capabilities of frontier models.
Closely liaise with research, engineering and cross-functional teams to determine which integrations are production-ready for inclusion in major model releases.
Degree in Computer Science, Machine Learning, or a related field; advanced degree (MS/PhD) preferred with a strong publication record in top-tier AI conferences.
Experience with multimodal post-training workflows and data pipelines, particularly for agentic systems and tool use.
Hands-on experience applying post-training at scale using distributed training frameworks (e.g., multi-node GPU environments).
Demonstrated experience improving model capabilities in areas such as reasoning, tool use, and multi-agent coordination that achieve SOTA results.
Proven track record of open-source contributions related to agentic systems or tool use (code, datasets, or models) on platforms such as GitHub or Hugging Face.
Publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, ECCV).
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Location: Thessaloniki, Greece
CENSUS is an internationally acclaimed Cybersecurity services
provider. We support the needs of multiple industries, providing IT and
OT security assessment services to public and private organizations
around the world, including international financial institutions and
Fortune 500 companies. Powered by cutting edge research, scientific
analysis and real-world engineering, we deliver unparalleled security
assessment services for software, devices, infrastructure and
organizations. Learn more about CENSUS at census-labs.com.
CENSUS
continues its successful paid internship program, allowing interns to
build up skills and gain experience in the area of Vulnerability
Research. The intern will join our Thessaloniki team.
Remote
working as well as on-site working options (hybrid) are offered for the
internship.
Requirements
Background knowledge in software security (Academic or Professional)
Application debugging skills
C and Python development skills
x86 or x86_64 Assembly skills
Good understanding of at least two operating systems (Microsoft Windows, GNU/Linux, Android, MacOS or iOS)
Systems programming skills
Good understanding of networking and TCP/IP concepts
Also, any of the following (not strictly required) skills will be considered a plus:
Reverse engineering
Code auditing
Familiarity with IDA Pro or Ghidra
Candidates that successfully complete the internship program are offered a full time position with CENSUS.
CENSUS provides:
A
collaborative
work
environment: you will be working among exceptional engineers, highly
experienced in the field of Cybersecurity, that value teamwork and
knowledge sharing.
An
efficient
work environment:
you will be provided with access to the necessary technology, training
and resources in order to achieve your goals. CENSUS delivery processes
will make sure that the output of your work is of high quality and
presented in the best possible manner.
An environment for
personal development:
instead
of sticking to a project or a role, we purposefully make sure that you
gain experience by working on different projects and grow by practicing
different roles.
A
creative
work environment: our
engineers propose solutions to some of the most challenging
technological problems, contribute to many of the company’s processes
and tools, and perform leading IT Security Research with results
published on major conferences and publications.
An
enjoyable
work
environment: beyond the competitive salary and benefits, we maintain a
friendly and enjoyable work environment for everyone, covering work at
the office, remote work and onsite work at the customer’s premises.
CENSUS
is an equal opportunity employer. The Company does not discriminate on
the basis of race, color, creed, pregnancy, religion, gender, national
origin, age, disability, marital, or any other legally protected status.
The Company also makes reasonable accommodations for disabled
employees. Finally, the Company prohibits the harassment of any
individual based on their protected status. This policy applies to all
areas of personnel actions including recruitment, hiring, training,
promotion, compensation, benefits, transfer, and social and recreational
programs.
#LI-Remote
Location: Germany
About Allucent™
At Allucent™, our mission is to shine a light on new therapies that improve lives. When you join our team, you’ll use your unique skills, expertise, and knowledge to forge meaningful partnerships with clients while helping them turn groundbreaking ideas into life-changing treatments.
If you’re passionate about advancing pharmaceuticals and biologics, fueled by an entrepreneurial spirit, and eager to collaborate with top minds across science, business, and operations, we’d love to connect. Together we can accelerate innovation and grow side by side, making a last impact on patients worldwide.
Together we
SHINE
. Find more information about our values.
The role
Bring your monitoring expertise to the forefront of innovation.
We are looking for a
Clinical Research Associate (CRA)
to join our A-team. As a CRA at Allucent™, you will independently control and monitor investigational sites, pro-actively detect issues, provide solutions to ensure clinical studies are performed according to the trial protocol and in compliance with SOPs, applicable regulations, and the principles of Good Clinical Practice.
As a
CRA
, you will take the lead on monitoring activities, owning your sites and relationships with investigators. You’ll be the bridge between sponsor and site, ensuring trial integrity while being supported by a collaborative, experienced team. This includes work related to regulatory affairs, site activation processes—including contracting and start-up activities—to ensure smooth and compliant study execution. You will travel throughout Germany.
Main responsibilities:
Independently manage all aspects
of monitoring for assigned clinical trials across study phases, including site initiation, routine monitoring, and close-out visits.
Ensure compliance
with protocols, GCP, ICH, SOPs, and applicable regulatory requirements.
Build strong site relationships
, acting as a primary point of contact and ensuring high-quality data collection.
Identify and resolve site issues
, escalating as needed to maintain trial integrity and patient safety.
Activities around
regulatory affairs, site activation
and
study-startup.
Requirements
To be successful you will possess:
You’re an experienced CRA ready to take the next step with a company that truly values your expertise and independence. You thrive in an agile, collaborative environment and want to be part of a team making a real impact.
Experience leading monitoring activities in complex trials, ideally in oncology or rare disease with a minimum of at least 5 years’ experience.
Strong understanding of
ICH-GCP
and
regulatory guidelines
.
Clear and confident communicator in
English
and
German.
Comfortable working independently and managing priorities.
Willingness to travel, as required (8 DOS per month).
Benefits
Benefits of working at Allucent include:
Comprehensive benefits package per location
Competitive salaries per location
Departmental Study/Training Budget for furthering professional development
Flexible Working hours (within reason)
Participation in our enriching Buddy Program as a new or existing employee
Internal growth opportunities and career progression
Financially rewarding internal employee referral program
Eligibility for our Spot Bonus Award Program in recognition of going above and beyond on projects
Eligibility for our Loyalty Award Program in recognition of loyalty and commitment of longstanding employees
Disclaimers:
*Our in-office work policy encourages a dynamic work environment, prescribing 2 days in office per week for employees within reasonable distance from one of our
global offices
.
“The Allucent Talent Acquisition team manages the recruitment and employment process for Allucent (US) LLC and its affiliates (collectively “Allucent”). Allucent does not accept unsolicited resumes from third-party recruiters or uninvited requests for collaboration on any of our open roles. Unsolicited resumes sent to Allucent employees will not obligate Allucent to the future employment of those individuals or potential remuneration to any third-party recruitment agency. Candidates should never be submitted directly to our hiring managers, employees, or human resources.”
#LI-BL1
Location: Canada; San Francisco; Europe; London; United States; United Kingdom; Toronto; Montreal
Workplace: Remote
WHO ARE WE?
Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!
Why this role?
To have the opportunity to collaborate with Cohere researchers and tools on designing and implementing novel research ideas and shipping state-of-the-art models to production. We have openings in teams covering base model training, retrieval augmented generation, data and evaluation, safety, and finetuning, to name a few; and we are open to receiving intern applications in any research area relating to LLMs to broaden your research connections while obtaining deep experience in a growing AI startup.
Please Note: To be eligible for a Research Internship, you must be currently pursuing a PhD in Machine Learning, NLP, or a related discipline. You need to be available for a full-time internship that lasts for 4-6 months.
As a Cohere Research Intern, you will:
- Conduct cutting-edge machine learning research, building and training large language models.
- Focus on research projects aimed at expanding the frontier of knowledge in language modelling and associate areas such as evaluation, multimodal models, optimisation etc.
- Disseminate your research results through the production of publications, datasets, and code.
- Contribute to research initiatives that have practical applications in Cohere’s product development.
You may be a good fit if you:
- Are currently pursuing, or in the process of obtaining, a PhD in Machine Learning, NLP, Artificial Intelligence, or a related discipline. We will also consider exceptional non-PhD candidates.
- Are eligible for work authorization in the country of employment at the time of hire and maintain ongoing work authorization throughout the internship period.
- Have experience using large-scale distributed training strategies, data annotation and evaluation pipelines, or implementing state of the art ML models.
- Are familiar with autoregressive sequence models, such as Transformers.
- Have strong communication and problem-solving skills with the ability to convey complex research findings clearly and succinctly.
- Have knowledge, or are knowledgeable, of programming languages such as Python, C, C++, Lua, or related languages.
- Have knowledge of related ML frameworks such as JAX, Pytorch and Tensorflow.
- Have previous experience in building systems based on machine learning and deep learning techniques.
- Demonstrate passion for applied NLP models and products.
Preferred Qualifications:
- Demonstrated expertise through publications in top tier venues in fields such as machine learning, NLP, artificial intelligence, computer vision, optimization, computer science, statistics, applied mathematics, or data science.
- Proven ability to tackle analytical problems using quantitative methodologies.
- Proficiency in handling and analysing complex, high-dimensional data from various sources.
- Experience in applying theoretical and empirical research to real-world problem-solving.
FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS:
- A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
- Full health and dental benefits, including a separate budget for mental health.
- RRSP matching, 401K, Pension Scheme.
- 100% Parental Leave top-up for up to 6 months, for either parent.
- Annual enrichment benefits:
Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
Education & learning stipend for conferences, courses, and coaching.
- 6 weeks of paid vacation (30 working days!)
- Budget for traveling to other offices if you are remote, plus an annual company offsite.
HOW AND WHERE WE WORK:
- Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.
- For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
- For those not near an office: a co-working benefit so you can work alongside others in your city.
- Everyone receives a $500 home office stipend to set up your workspace properly.
If any of the above doesn’t line up exactly with your experience, we still encourage you to apply.
We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs.
We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.
УдалённоUnited Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus
УдалённоBangalore, India
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
Настройте подбор, и подходящие вакансии будут приходить в Telegram.
УдалённоUnited Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus
УдалённоUnited Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus
УдалённоUnited Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus
УдалённоСтажёрThessaloniki, Greece
УдалённоGermany
УдалённоСтажёрCanada; San Francisco; Europe; London; United States; United Kingdom; Toronto; Montreal; We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities