Условия и бонусы:
— Фултайм, удаленно.
Наши ожидания:
— 5+ лет коммерческой backend-разработки;
— 3+ лет разработки на Go;
— глубокое понимание concurrency в Go (goroutines, channels, context);
— понимание принципов микросервисной архитектуры;
— опыт построения event-driven систем;
— опыт работы с очередями и брокерами сообщений;
— уверенная работа с MySQL (индексы, транзакции, оптимизация);
— понимание финансовой арифметики (decimal, точность вычислений, отсутствие float-ошибок);
— опыт работы с Redis;
— понимание принципов построения low-latency систем;
— опыт работы с Docker и Git;
— уверенная работа в Linux-окружении.
GTE is the world’s fastest decentralized trading venue, backed by GSR, IMC, Flow Traders, and other top-tier market makers and VCs. The company offers trading from anywhere in the world, 24/7, permissionless, with no brokerage account required. The team includes talent from Jump, Citadel, HRT, GSR, Google, Palantir.
Задачи:
— Design low-latency ingestion pipelines, ensuring message ordering, deduplication, and backpressure handling.
— Implement consensus-based failover and snapshotting for resilience and leader coordination.
— Manage memory layout, allocation strategy, and hot-path locality.
— Coordinate with infrastructure team to handle data persistence, cold storage, and historical reindexing.
Требования:
— Remarkable backend engineering experience in production environments in Rust or C++.
— Strong grasp of distributed systems design: log replication, failure recovery, snapshotting, consensus (Raft/Paxos).
— Deep familiarity with event-driven architectures: ordered delivery, deduplication, replay, state machines.
— Experience with high-throughput async systems such as tokio, epoll, io_uring.
— Proficient with memory-safe performance tuning: preallocation, arena allocators, cache-line alignment.
— Comfortable working close to the metal: Linux internals, syscall-level tuning, and debugging with perf.
Плюсом будет:
— Experience with Go in production environments.
— Prior work on crypto data indexers, block explorers, or DeFi.
— Knowledge of low-level blockchain primitives (e.g., Merkle proofs, EVM logs, calldata parsing).
— Contributions to open-source Rust or crypto infrastructure projects.
— Exposure to consensus layer mechanics or validator/network observability.
Условия:
— Remote work or office in NYC (relocation help may be provided in some cases).
— Salary 150-250k USD/year gross + tokens (up to 750k total compensation by current valuation).
Location: United States, Madison, WI
Why Sony Interactive Entertainment?
Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.
Sr. Software Development Engineer In Test, ML/AI
At SIE, we believe in making play safer for everyone. Within our Information Security team, we protect our people, platforms, and products with smart, scalable, and thoughtful solutions. Our mission is to provide clear, actionable risk and security insights that guide the business and enable amazing player experiences.
We’re building a team that thrives on collaboration, curiosity, and delivering real value. Come help us make a difference!
Overview
We are hiring a Sr Software Engineer in Test specializing in ML/AI quality, including automation for model evaluation, LLM-assisted test generation, and validation of AI-powered workflows. The role includes guiding quality strategy and developing automation frameworks. You will also manage implementation for complex, cross-functional, machine learning-powered products and services. This role involves more than test development. You will lead quality initiatives from start to finish, ensuring teams stay synchronized, dependencies are managed, and releases are delivered confidently. You will work closely with ML, engineering, product, and infrastructure teams. You will shape how quality is built, monitored, and expanded while leading embedded QE efforts within projects.
What you’ll do
Define and complete quality strategies, test plans, and automation coverage for ML-powered services and platform components.
Use LLMs and other AI-assisted techniques to generate, expand, and maintain high-value test cases for ML-powered workflows.
Design scenario-based test suites for AI features, including adversarial prompts, edge cases, ambiguous inputs, and underrepresented user scenarios.
Lead QE efforts for multi-functional projects, driving risk assessment, dependency management, and release readiness.
Design, develop, and maintain scalable automation frameworks for backend services, APIs, and ML inference systems using Python and/or Java.
Build automated validation for ML and LLM outputs, including ranking behavior, score distributions, prompt/response quality, hallucination indicators, and probabilistic model evaluation.
Debug test failures, service anomalies, model inconsistencies, and AI behavior regressions to identify root causes and drive resolution.
Perform functional, integration, regression, API, end-to-end, performance, and reliability testing for distributed systems.
Improve automation reliability, reduce flakiness, and optimize execution efficiency.
Partner with engineering and ML teams to integrate automated testing into CI/CD pipelines and release workflows.
Collaborate across teams to establish scalable quality standards, tooling, and guidelines.
Required qualifications
Bachelor’s degree in Computer Science or equivalent
5+ years of experience as an SDET or QE engineer focused on backend and distributed systems.
Experience using LLMs to generate, transform, and prioritize test cases for AI-powered experiences.
Experience with AI evaluation tooling, prompt evaluation frameworks, model monitoring, or human-in-the-loop review workflows.
Strong experience testing RESTful APIs, microservices, and distributed architectures.
Proficiency in Python, Java, JS or similar languages for automation development.
Hands-on experience with automation frameworks such as pytest, JUnit, Selenium, Playwright, Cypress, or Appium.
Experience with CI/CD systems and test pipelines (Jenkins, GitHub Actions, etc.).
Experience with cloud and container technologies (AWS, GCP, Kubernetes, Docker).
Familiarity with databases, monitoring, and observability tools.
Strong understanding of SDLC, Agile methodologies, and release processes.
Excellent problem-solving, debugging, and communication skills.
Preferred qualifications
Experience validating ML outputs using statistical analysis or scenario-based testing approaches.
Familiarity with ML infrastructure, data pipelines, or model-serving platforms (Seldon, KServe, Ray Serve, etc.).
Prior work in content moderation ML, security, fraud detection, or adversarial ML.
Experience testing high-scale, low-latency online services.
Experience with Databricks or similar ML platform tooling.
Familiarity with Node.js, React, or modern frontend technologies.
Experience testing mobile, console, or other non-PC platforms.
What sets you apart
Strong combination of automation engineering and delivery ownership.
Ability to drive quality across complex cross-functional initiatives.
Practical understanding of how to test non-deterministic AI systems and separate model variance from quality regressions.
Proven risk management and dependency coordination skills.
Ability to influence engineering teams and promote quality guidelines.
Passion for scalable, reliable, and maintainable automation systems.
At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.
Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location.
In addition, this role
is eligible
for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products.
This role also may be eligible for a bonus package.
Click
here
to learn more.
The estimated base pay range for this role is listed below.
$152,500
—
$228,700 USD
Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.
Please refer to our
Candidate Privacy Notice
for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.
Equal Opportunity Statement:
Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.
We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.
Location: San Francisco; Palo Alto; London; Berlin; Belgrade; New York City
ABOUT THE ROLE
The Cloud Infrastructure team owns the foundational cloud primitives and deployment models that power Perplexity's products, from multi-tenant public cloud to single-tenant and on-premises solutions for enterprise customers.
As Perplexity grows its Computer and Enterprise products, this team builds and operates the security, isolation, and compliance layers that customers depend on. We provide the deployment topologies, multi‑region infrastructure, and core services that enable Perplexity to run reliably and efficiently for both consumer traffic and large enterprises.
KEY RESPONSIBILITIES
- Own the roadmap and technical strategy for agent-driven cloud infrastructure management.
- Design and operate Perplexity’s cloud networking fabric, including VPC architectures, private connectivity, and peering with hyperscalers and neocloud providers to support low-latency, high-throughput AI workloads.
- Architect and scale compute platforms (Kubernetes/EKS, autoscaling groups, and mixed CPU/GPU fleets) to efficiently serve online request traffic and background workloads across regions.
- Build and maintain secure, isolated deployment topologies for multi-tenant, single-tenant, and customer‑owned cloud (BYOC) environments, including cross-account networking, identity, and policy guardrails.
- Implement and evolve multi-region strategies for availability, failover, and data locality, including traffic routing, regional capacity planning, and disaster recovery playbooks.
- Partner with security to deliver enterprise controls such as BYOK/KMS integrations, network isolation, and auditability required for regulated customers.
- Develop automation, tooling, and runbooks that make day‑2 operations (provisioning, upgrades, incident response) predictable and repeatable for Perplexity products across all environments.
QUALIFICATIONS
- Deep experience designing and operating cloud infrastructure on AWS (VPC design, routing, security groups, load balancing, private connectivity).
- Strong background with Kubernetes/EKS and container orchestration, including multi‑cluster, multi‑region, or multi‑account setups.
- Hands-on experience with cloud networking and peering (VPC peering, Transit Gateway, private link/service endpoints, or similar constructs in neoclouds).
- Experience building or operating secure, isolated environments for enterprise customers (single‑tenant, BYOC, or on‑prem), ideally including BYOK/KMS integrations and compliance constraints.
- Proficiency with infrastructure as code (Terraform) and strong software engineering skills in at least one of Python, Go, or Rust for automation and tooling.
- Strong debugging and incident management skills across distributed systems (networking, compute, and platform layers), with a track record of driving root‑cause analysis and long‑term fixes.
- 7+ years of industry experience building and operating production cloud infrastructure, including leading the design of complex systems or migrations.
If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.
Location: Hamburg
Workplace: Hybrid
adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we've become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually.
Ensuring Authenticity for Billions of Daily Rewards
Industry reports suggest 25 percent of global mobile ad spend is lost to fraudulent activities like click farms, fake installs, SDK spoofing, and emulator farms. At adjoe, we define our platform through trust and proactive engineering. We build high-performance defenses that guarantee accurate reward attribution, ensuring every interaction is authentic. This creates a sustainable value exchange that empowers our partners to grow with confidence.
The Anti-Fraud team develops systems that detect and prevent malicious activity at scale. Our custom Android and iOS SDKs analyze device integrity for modifications like Xposed frameworks, Magisk modules, and jailbroken devices. Supporting these, Go microservices and DynamoDB deliver millisecond-level responses, while Kafka and SQS process billions of daily events in real time. This infrastructure protects publisher margins and ensures a trustworthy platform for all users.
Your Mission & Who We Are Looking For:
- Architecting High-Scale Go Microservices: You have several years of experience as a software architect or senior software developer with outstanding Go expertise in professional backend environments. You will maintain our microservices architecture and scale the platform beyond hundreds of millions of monthly active users using cloud infrastructures like AWS, Azure, or Google Cloud.
- Event-Driven Pipeline Engineering: You have experience building event-driven systems using Kafka and SQS/SNS. Your mission is to establish reliable asynchronous microservice communication, collect billions of daily API events, and aggregate them in Kafka streams so they can be queried from our data lake in a matter of seconds.
- Low-Latency NoSQL Database Design: You bring extensive experience with large-scale key-value databases such as DynamoDB, Cassandra, or ScyllaDB. You will deploy this knowledge to optimize our database layer, ensuring we consistently deliver few-millisecond response times to block fraudulent transactions in real time.
- Technical and People Leadership: You have a proven track record of managing people, mentoring developers, and setting technical direction in fast-changing environments. You will lead our backend engineers, establish high engineering standards, and run peer code reviews to foster alignment across our international team.
- Adversarial Fraud Investigation: You think like a hacker and naturally find ways around systems that block your progress. You will investigate novel fraud complaints, collaborate with mobile developers to reproduce exploits or cheats, and continuously improve our systems to counter evolving Android and iOS threats.
- Plus: Mobile Development Fundamentals: Basic knowledge of Android or iOS development is a plus. This understanding will help you collaborate with mobile engineers to analyze device integrity modifications like Xposed frameworks, Magisk modules, and jailbroken devices.
🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team.
What’s in It for You?
At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day.
- Go Big. Own projects with impact on 770M users and push adtech boundaries.
- Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum.
- Be Direct. Solve problems openly and collaborate across teams.
- Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other.
- Have Fun. Celebrate wins, enjoy daily victories, and bring your energy.
We welcome applications from people who will contribute to the diversity of our company.
Location: Montenegro; Slovenia; Slovakia; Moldova; Romania; Poland
The position is open for a global, publicly traded AdTech market leader. The company's platforms handle over 1 trillion requests per day, operating within a highly optimized real-time cloud architecture across dozens of servers and processing terabytes of data daily.
The engineering team focuses on intense performance optimization, low-latency infrastructure, asynchronous data streaming, and cutting-edge GenAI research and development.
Salary: upto
$5,000 USD / month.
Format:
Full-time. Hybrid (Budva, Montenegro) or 100% Remote globally
Contract Type:
B2B Contract
Responsibilities
Design, scale, and maintain real-time advertising bidding systems (DSPs, RTB Exchanges, and SSP platforms).
Optimize backend services using Java (Spring Boot / WebFlux) and Go (Golang) to meet strict low-latency SLA/SLO targets.
Build and manage data-intensive architectures utilizing high-load storage solutions (Aerospike, ClickHouse) and event-driven messaging (Apache Kafka).
Participate in R&D initiatives involving GenAI, integrating Agentic AI frameworks (LangChain, LangGraph, N8N) for workflow automation and predictive analytics.
Take full ownership of features end-to-end, contributing to the frontend layer (React / TypeScript) for internal tools and dashboards when required.
Requirements
5+ years of commercial software development experience with Java as the primary language.
Deep knowledge of the Spring ecosystem (Boot, Data, MVC, Security, Cloud) and strong practical experience with reactive/asynchronous programming (Spring WebFlux / Project Reactor).
Solid understanding of distributed systems, concurrency, and performance tuning at the JVM level.
Strong verbal English skills at B2 level or higher, with the ability to explain architectural decisions and collaborate directly with a global engineering team during voice calls.
Location outside of the Russian Federation due to contractual and payment restrictions. Candidates from Belarus are eligible only if they possess an active legal entity/IP in Georgia or Europe for international payments.
Commercial programming experience or strong familiarity with Go (Golang).
Hands-on experience with high-load and Big Data tools including Apache Kafka, ClickHouse, and Aerospike.
Real-world experience or deep interest in LLMs and AI orchestration tools such as LangChain, LangGraph, or N8N.
Familiarity with frontend development using ReactJS and TypeScript.
Benefits
Opportunity to work on production infrastructure handling 1 trillion + daily requests.
Work within a team of senior engineers with direct impact on the platform's architecture.
Choice between a fully remote schedule or a hybrid format from the office in Budva, Montenegro.
Stable monthly payments in USD via international B2B contracts.
Location: Stockholm
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
THE ROLE:
We’re looking for an Engineering Manager to lead a group of highly experienced engineers. This is a hands-on leadership role where you’ll spend roughly half your time on technical contribution and half on people management, depending on the need. You’ll work closely with the team to set direction, remove blockers, and foster a strong engineering culture as they tackle complex systems challenges in distributed computing, large-scale data handling, and performance optimization.
YOU MAY BE A FIT IF:
- You have at least 10 years of industry experience, including 3 years in a leadership role
- You’ve built high-performance distributed systems at a large scale
- You have a strong background in cloud infrastructure
- You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.)
- You’re proficient in systems-level languages such as Rust, C, C++, or Java
- You’re an experienced engineering leader who thrives close to the work and enjoys building alongside your team when needed
- You earn trust through technical depth, communicate with clarity, and help great engineers move fast and make sound decisions
- You thrive in a fast-paced environment and are pragmatic, calm under pressure, and focused on impact
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
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: 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
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: 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.
seniorUnited States, Madison, WI
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.
San Francisco; Palo Alto; London; Berlin; Belgrade; New York City
Гибридlead🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team
УдалённоseniorПротиворечивые условия: Candidates from Belarus are eligible only if they possess an active legal entity/IP in Georgia or Europe for international payments
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
УдалённоГеография найма не уточнена
УдалённоAbu Dhabi, United Arab Emirates
УдалённоAmsterdam, Netherlands
УдалённоBarcelona, Spain
УдалённоSao Paulo, Brazil
УдалённоDublin, Ireland
УдалённоLondon, United Kingdom
УдалённоDubai, United Arab Emirates
УдалённоUnited Kindom, United Kingdom
Все вакансии в одном месте - страница 9 · Job Hunters
