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
Break down the key responsibilities in bullet points. It’s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.
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
Break down the key responsibilities in bullet points. It’s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.
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
Break down the key responsibilities in bullet points. It’s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.
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
Break down the key responsibilities in bullet points. It’s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.
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
Break down the key responsibilities in bullet points. It’s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.
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
Break down the key responsibilities in bullet points. It’s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.
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
Break down the key responsibilities in bullet points. It’s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.
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
Break down the key responsibilities in bullet points. It’s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.
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: Belgrade, Serbia
Workplace: remote
At Novakid, we’re building one of the world’s most engaging online English-learning platforms for kids. Today, we serve 100,000+ students and work with 4,000 + teachers across 15+ countries.
We’ve already proven the demand. Now we’re scaling the platform, expanding AI-driven learning experiences, and rethinking how our backend should evolve for the next stage of growth.
This is where you come in.
About the Role
Novakid is hiring a
Head of Data & Analytics
to lead the next stage of our analytics evolution — transforming a strong existing foundation into a modern, AI-enabled decision system that scales with the business.
This is a strategic leadership role with broad scope: you'll own the analytics organization, the technology transformation, data science, and the data culture across the company. You won't be starting from scratch — you'll be accelerating a transformation already underway.
What You'll Lead
Analytics Strategy & Operating Model
Define how data and analytics supports growth, product development, commercial performance, and operations. Shape what is self-serve, AI-assisted, automated, and expert-led.
Analytics Team Leadership
Lead a team of analysts embedded across product squads and business functions. Raise the bar on speed, strategic impact, and self-service enablement while keeping analysts focused on the highest-value work.
AI-Powered Analytics
Scale practical AI use cases: natural-language data access, AI-assisted insight generation, anomaly detection, automated reporting, and productivity tooling for analysts and stakeholders.
Experimentation & A/B Testing
Strengthen Novakid's experimentation culture — making it faster and easier to design, launch, measure, and learn from experiments without heavy analyst involvement at every step.
Data Science
Build a structured, high-impact data science capability spanning ML for business use cases, forecasting, experimentation support, AI-powered product features, and research for new learning experiences.
Metric Governance & Data Foundation
Drive clearer KPI ownership, stronger documentation, and a trusted semantic layer across Product, Growth, Sales, Marketing, and Finance — reducing ambiguity and conflicting interpretations.
What Success Looks Like
Faster turnaround on common business questions and broader stakeholder self-service
A modern AI-enabled analytics capability adopted across the company
A stronger experimentation practice with less dependency on analyst bandwidth
Clear KPI ownership and trusted, well-documented data
A well-structured data science function supporting both business and product innovation
Strong executive confidence in data-driven decision-making
What We're Looking For
Significant leadership experience in analytics, BI, or data functions within high-growth digital businesses
Proven track record transforming analytics toward scalable, self-serve, AI-enabled models
Strong technical grounding in modern data stacks, cloud warehouses (we use BigQuery), BI tooling, and semantic modeling
Hands-on SQL fluency and solid understanding of analytics engineering principles
Experience leading or reshaping embedded analyst teams
Practical, hands-on experience applying AI in analytics at scale
Experience building or rebuilding a data science function spanning business support and product features
What we offer…
Fully remote work
A chance to shape the future of AI-driven education.
A fun, dynamic team that loves building innovative products.Unlimited holidays – because we trust you to deliver.
Bonuses and stock options – we grow together
Location: Beograd, Serbia
Workplace: remote
Novakid is an online English platform for kids — 100,000+ students, 2,500+ teachers, 15+ countries. Live classes run around the clock across time zones, which sets the technical bar: low latency, high availability, and a backend that holds up at real scale.
We’ve built a working platform. The next chapter is making deliberate architectural choices about how it should evolve.
The role
We’re hiring a Principal Backend Engineer to take ownership of backend architecture as a hands-on technical leader. No direct reports. About half your time is in the code — reference implementations, critical components, refactors. The other half is the harder work: deciding what to build, what to buy, what to defer, and why.
Our backend today is a Python core (FastAPI, SQLAlchemy, Celery, Postgres, Redis), surrounded by services and event-driven flows, with a growing AI layer. It runs primarily on AWS, with GCP for data and AI workloads. There are real architectural questions to answer: how to evolve the monolith, how to set service boundaries, how to design for geo-distribution as we grow, and how to integrate AI without accumulating debt. We’re looking for someone who treats those questions seriously — researches before deciding, thinks in tradeoffs, writes things down.
What you’ll work on
Backend architecture standards and major technical decisions across teams
The path from monolith toward a more modular, service-oriented backend
Service blueprints: API conventions, EDA patterns, testing, observability, deployment
Cloud architecture across AWS (primary) and GCP, including multi-region and geo-distributed designs
High-load, real-time systems: live class infrastructure, latency budgets, caching, capacity
Buy vs. build vs. assemble — knowing when a managed service, a no-code tool (Retool, n8n), or an agentic-coding POC (Claude Code, Cursor) is the right call, and when it isn’t
Production code: components, refactors, POCs, and selected product-critical features
What we’re looking for
7+ years of backend engineering, deeply hands-on in Python
Production experience with FastAPI, SQLAlchemy, Celery, Postgres, Redis
Strong AWS architecture experience (EKS, Lambda, RDS, SQS/SNS/EventBridge, and so on); working knowledge of GCP a plus
Experience designing high-load, latency-sensitive, and geo-distributed systems
Pragmatic judgment on buy vs. build vs. assemble — managed services, no-code, and agentic tooling as first-class options, not shortcuts
A deliberate working style: you research, weigh tradeoffs, document decisions, and explain them clearly to engineers and non-engineers alike
Nice to have
LLM integrations in production (OpenAI, Anthropic, Google AI) — evaluation, cost, reliability
Active use of agentic coding tools (Claude Code, Cursor) as part of how you ship
EdTech or other high-scale consumer platforms
Stack
Python · FastAPI · SQLAlchemy · Celery · Postgres · Redis · Kubernetes (EKS, GKE) · AWS · GCP · SQS/SNS/EventBridge · Pub/Sub · OpenAI · Anthropic · Google AI
What we offer…
Fully remote work (core hours GMT+3).
A chance to shape the future of AI-driven education.
A fun, dynamic team that loves building innovative products.Unlimited holidays – because we trust you to deliver.
Bonuses and stock options – we grow together.
Location: Tbilisi, Georgia
Workplace: remote
Novakid is on a mission to build the best online education platform for kids worldwide. We’ve already got over 100,000 students and 4,500 teachers making learning awesome in over 15 countries in Asia, Europe and Latin America. But we’re not stopping there—we need your help to take things to the next level!
We are looking for an experienced Product Analyst with strong SQL skills and solid experience in working with business data who can apply his/her expertise to help us grow.
You will:
Work closely with the acquisition team to support them with accurate, reliable, and timely data insights
Own and drive growth of key acquisition funnel metrics
Develop and maintain dashboards, perform ad-hoc analyses and deliver actionable insights to the acquisition team
Ensure high quality of data collection and contribute to technical decisions that improve data pipelines and reporting systems
Apply machine learning techniques to improve acquisition efficiency
Collborte on development and evaluation of ML models (feature design, validation, interpretation of results)
Use data-driven approaches to optimise user acquisitionSupport experimentation with advanced methods
You have:
3+ years of relevant experience as a Product Analyst (preferably in a B2C or fast-growing company)
Excellent SQL skills with hands-on experience in relational and columnar databases (we use Google BigQuery)
Experience in building data models and data martsExperience with BI tools (Metabase, Tableau, PowerBI — we primarily use Metabase)
Strong analytical mindset and good understanding of statistical methodsHands-on experience with A/B testing, from design to statistical evaluationKnowledge of Python for data analysis (pandas, numpy, scikit-learn, etc.)
Experience applying ML in business contextsUnderstanding of causal inference / uplift modeling is a strong plus
Good presentation and communication skills to explain findings clearlySolid English skills for business communication (B1+)
What we offer:
Fully remote work.
A chance to shape the future of AI-driven education.
A fun, dynamic team that loves building innovative products.
Unlimited holidays – because we trust you to deliver.
Bonuses and stock options – we grow together.
Location: Belgrade, Serbia
Workplace: remote
NovaKid is a global leader in online English education for children aged 4–12, serving 100000+ students across 50+ countries. As the Product Manager for Engagement & AI Game-Based Learning, you will own the "non-live" student experience.
Your goal is to transform the Novakid Kid’s Area from a supplementary area into a significant driver of engagement for young kids. You will lead the development of self-guided English learning games and integrate cutting-edge AI-based self-practice tools that encourage children to speak more, practice safely, and stay motivated between their 1:1 teacher sessions.
Focus: Kid’s Area, Self-Learning Games, AI Features, Learning Engine
What you’ll do
Lead a small team of designers and developers (with access to analytical and research resources).
Design and scale features like Pandy AI Tutor to provide 24/7, judgment-free speaking practice for students across various proficiencies.
Own the roadmap for current and future gamified worlds, focusing on LLM based learning mini-games that reinforce curriculum-aligned vocabulary and grammar.
Use AI to create adaptive learning paths that adjust game difficulty and content in real-time based on a child’s performance in both live classes and self-study (Learning Engine).
Work with engineering to refine Speech-to-Text and AI prompting logic to maximize student speaking time—aiming for the high-engagement levels seen in AI-only learning models.
Design and manage the "Economy of Fun," including avatars, star rewards, and other gamification features that compete for a child's attention against mainstream apps.
Work closely with designers, engineers, curriculum developers, and teacher operations to turn user insights into high-quality educational content and engaging UX.
What you’ll have
4+ years’ experience in a PM role.
Hands-on experience in AI-powered features (prompt engineering, conversational AI, or adaptive algorithms).
Strong background in mobile gaming or highly gamified EdTech, with a deep understanding of reward systems, level progression, and retention hooks for kids.
Proven ability to build interfaces for 4–12-year-olds that are intuitive, safe, and require zero parental intervention.
Proficiency in analytical tools to analyze engagement metrics and game-completion rates.
Manage the Agile process with our engineering team, ensuring that prototypes are delivered and scaled with technical excellence.
You thrive in a 100% remote, distributed team environment and are a master of tools like JIRA and Slack.
Excellent spoken and written English.
What we offer
Fully remote work
A chance to shape the future of AI-driven education
A fun, dynamic team that loves building innovative products
Unlimited holidays, because we trust you to deliver
Location: Jeddah, Saudi Arabia; Riyadh, Saudi Arabia; Lusail, Qatar; Dubai, United Arab Emirates; Hyderabad, India; Lahore, Pakistan
Eram Talent is seeking a Systems & Digital Operations Specialist to join our team in Saudi Arabia. The Systems & Digital Operations Specialist is responsible for the effective day-to-day administration, reliability, and continuity of TKS digital systems, user devices, and classroom technology that support teaching, learning, admissions, communications, and school operations. The role also provides operational support to the Operations team, contributing to school-wide readiness, coordination, and delivery. This is a non-managerial, hands-on role focused on execution, support, and coordination in line with TKS policies and procedures.
Key Responsibilities:
Administer and support core school systems including
PowerSchool
, Toddle, and Google Workspace for Education.
Manage user accounts, permissions, and access controls in line with school policies and data protection standards.
Monitor system availability and ensure timely escalation of technical issues.
Support setup, configuration, and maintenance of devices (iPads, laptops, and peripherals).
Maintain device inventory, lifecycle management, and coordinate repairs or replacements with vendors.
Provide support for classroom and shared-space AV systems (projectors, displays, conferencing tools).
Assist teachers and staff with basic troubleshooting for lessons, meetings, and school events.
Support academic year readiness including onboarding, class setup, and device allocation.
Maintain documentation, track tickets, licenses, warranties, and vendor coordination.
Provide operational and cross-functional support to Academic, Admissions, HR, and Operations teams.
Requirements
Bachelor’s degree in IT, Computer Science, or a related field (preferred).
Proven experience in IT support, systems administration, or digital operations.
Hands-on experience supporting user devices such as laptops and tablets.
Familiarity with systems like
PowerSchool
, Toddle, or similar SIS/LMS platforms.
Experience working with Google Workspace for Education or similar tools.
Strong organizational and documentation skills.
Ability to follow procedures and escalate issues appropriately.
Experience supporting non-technical users, ideally in a school environment.
Basic knowledge of AV/classroom technology systems.
Understanding of data protection, confidentiality, and IT security practices.
Jeddah, Saudi Arabia; Riyadh, Saudi Arabia; Lusail, Qatar; Dubai, United Arab Emirates; Hyderabad, India; Lahore, Pakistan
Location: Australia
Workplace: remote
Overview
Are you passionate about languages, writing, and quality evaluation? We are launching an exciting language evaluation project and are looking for Mandarin-speaking experts to join our team.
In this role, you will contribute to training AI systems to better understand, generate, and refine language by performing structured evaluation and writing tasks, all from the comfort of your home and on a flexible schedule.
What you will do:
- Evaluate AI-generated responses for accuracy, grammar, and cultural relevance.
- Identify issues and provide refined, high-quality rewritten responses.
- Create natural prompts and responses in Mandarin to improve conversational datasets.
- Collaborate with global teams to help improve AI language models.
Project Details:
- Duration: 4 weeks.
- Rate: $40USD/hour
- Commitment: ~10 to 20 hours/week (flexible schedule).
- Job Type: Freelance contract.
- Location: Remote
Requirements:
- Background as a teacher (preferred but not a must) or experience in teaching/writing in Mandarin.
- Excellent written communication and strong grammatical accuracy.
- Familiarity with cultural nuances in Mandarin.
- Comfortable with structured tasks such as: preference ranking (factuality & locality), prompt-response writing, grammaticality checks, provision & improvement of text.
Note: Please do not use VPNs or IP-masking tools during the recruitment process — our security system requires accurate regional verification.
Job reference: #L1-CC1
Why Join Welo Data?
✨ Limitless Flexibility
Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.
🌱 Limitless Growth
Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.
🌍 Limitless Support
Be part of a global contributor community with responsive guidance and support.
💡 Real Impact
Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.
How to Apply?
Apply now by answering a few quick questions to join our database and become part of our growing community.
About Welo Data
Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.
At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.
Location: Warsaw, Poland
Workplace: remote
At Novakid, we are on a mission
to build the world’s best online education platform for children. With over 100,000 students and 4,000 teachers, Novakid is already one of the most popular language learning platforms for children aged 4–12 across Europe and Asia.
About the role
We are building a new interactive entertainment project for families (parents + children) — with YouTube as the main platform and content home.
Short-form content (TikTok, Instagram Reels, YouTube Shorts) will serve as the acquisition engine: hooks, teasers, cliffhangers, and emotional moments designed to drive viewers to the main YouTube episodes.
You will own the creative direction for both long-form and short-form — ensuring every piece of content works together as a system, not separately.
Before we invest in full production, we will first test concepts using short-form content to measure audience demand, engagement, and intent to watch longer episodes.
Cultural & Audience Insight
Ensure concepts resonate with parents culturally and emotionally, with a focus on the TR market
Anticipate cross-cultural interpretation, humor, and sensitivity
Keep Novakid relevant to real parent conversations, not marketing narratives
What you have done before (real experience we need)
You have concepted and led production of long-form YouTube content (8–20+ min) — episodic, story-driven, with clear hooks and payoff.
You have successfully repurposed long-form content into short-form trailers/teasers that drove measurable traffic back to YouTube.
You have tested content concepts using only short-form (TikTok, Reels, Shorts) before investing in full episodes — and can show examples of how you made that decision.
You understand YouTube organic metrics (CTR, retention, AVD) and short-form metrics (completion rate, shares, comments) — and how they relate.
You have worked on projects with participatory or community elements (even simple ones like comments shaping next steps).
Key responsibilities
YouTube first: Everything starts with the long-form episode. Short-form serves it, not the other way around.
Test fast: Use short-form to validate concepts before building full episodes.
Own the creative vision from title/thumbnail to final frame of each episode.
Collaborate with production teams but stay responsible for viral instincts and audience psychology.
Analyze performance across both formats and iterate quickly.
Must-have qualifications
Portfolio with long-form YouTube content you concepted (show retention, CTR, or growth if possible).
Proven ability to drive traffic from short-form to long-form (examples required).
Deep understanding of TikTok, Reels, and YouTube Shorts as acquisition tools, not standalone entertainment.
Obsessed with hooks, pacing, cliffhangers, and payoff.
Strong interest in parenting, family dynamics, or human stories involving children
Requirements:
Experience leading video projects from concept to final delivery.
Experience with family, parenting, or kids content.
Basic editing or thumbnail design sense.
Experience building a YouTube channel (other Social Media channels) from zero.
C1 level English
We offer:
Opportunity to work in an innovative, fast-growing edtech company.
A creative and collaborative work environment.
Comprehensive professional development and leadership growth opportunities.
The chance to have a meaningful impact on the lives of young learners around the world.
100% Remote work
Unlimited holidays
Bonuses and stock options
УдалённоAmsterdam, Netherlands
УдалённоBarcelona, Spain
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.
УдалённоBeograd, Serbia; Live classes run around the clock across time zones, which sets the technical bar: low latency, high availability, and a backend that holds up at real scale; Fully remote work (core hours GMT+3)
