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Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: The Encodings Infra team maintains the libraries that engineers and researchers across Anthropic use to encode text and multimodal data into a form that Claude can consume. It also determines Claude’s prompt shape: how a user’s turn is represented to the model, how Claude calls tools and receives tool results, and so on. As a Software Engineer on this team, you'll own the design and maintenance of these libraries—keeping their APIs intuitive, their performance sharp, and their abstractions solid enough that most of the org never has to think about encodings or prompt structures at all. You’ll have the satisfaction of knowing that your work enabled Claude to learn new ways of understanding the world. This role is unusually broad: your work will touch systems across the codebase, from pretraining to finetuning to the API, and you'll collaborate closely with both researchers and engineers to make sure new encoding ideas can move quickly from experiment to production. Responsibilities: Maintain and improve the encoding libraries used by engineers and researchers across Anthropic Run experiments to determine the optimal way to feed structured data into Claude without confusing it Design data structures and abstractions that shield most of the organization from the details of how encoded data works while enabling “power users” Adapt the encoding libraries to support new research directions as they emerge, and make sure that we can ship these research ideas to production Optimize encoding performance across the systems that depend on these libraries You may be a good fit if you: Have 5+ years of software engineering experience, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs Have familiarity with ML terminology and LLM architecture — you don't need to be an ML expert, but enough understanding to work effectively alongside researchers and understand the results of experiments Have experience carrying out complex refactors in large codebases Have strong communication skills and enjoy working closely with researchers and engineers to understand what they need Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Care about the societal impacts of your work Strong candidates may also have experience with: Tokenizers or other text/data encoding systems Maintaining a widely-used library over a long period of time Performance optimization Python and/or Rust Reinforcement learning or model training infrastructure Representative projects: Working with a research team to ship a new multimodal data type (audio, video, etc) to production Redesigning a core abstraction so that we can change how data is encoded into Claude without breaking downstream teams The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Paris; Amsterdam; Linz; Munich; London; Berlin ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE Mistral is looking for AI Scientists with deep expertise in engineering sciences and machine learning to push the frontier of AI-accelerated simulation. Within AI4Engineering Science, you will research and train foundational physics models which are substantially more capable than what exists today and can be fine-tuned for downstream applications by both customers and internal teams. You will work across the full research stack: curating high-fidelity simulation datasets, designing and training novel model architectures, and rigorously evaluating them against real engineering validation standards. Working closely with the broader research organization, you'll ensure the foundation models you build are general enough to become the backbone of many downstream products, not just a single point solution. This role builds on a strong, world-class foundation, and the goal is to take it further. You'll work one vertical at a time toward foundation models that genuinely transfer and fine-tune across engineering tasks, with high-quality simulation data pipelines, physics-based evaluation, and uncertainty / out-of-distribution estimation as first-class concerns. There's no inherited playbook for most of what's left to do: you'll help define the architectures, training strategies, and validation standards the team builds on, not just extend an existing one. WHAT YOU WILL DO - Research and train novel foundation models for physics simulation, pushing past today's state of the art in accuracy, generalization, and scale - Design and run large-scale simulation campaigns using domain-specific solvers to build the high-fidelity datasets foundational physics models need - Investigate architectures and training strategies (e.g. multi-fidelity training, pretraining objectives, scaling behavior) that let a single foundation model transfer and fine-tune well across diverse engineering tasks - Rigorously evaluate model coverage, accuracy, and robustness against industry validation standards, and diagnose failure modes arising from data gaps or architecture limitations - Stay on top of the latest developments in the scientific community and contribute to Mistral's standing at the frontier of AI-for-engineering research WHAT WE'RE LOOKING FOR - PhD or Master's in CS/AI or an engineering science: Mechanical Engineering, Electrical Engineering, Computational Fluid Dynamics, Structural Mechanics, EDA, Semiconductor Engineering, or a related field - Strong, hands-on machine learning expertise with a deep understanding of model architectures, training dynamics, and evaluation methodology is core to this role - You have developed ML methods for simulation or surrogate modelling - You write clean, readable Python code and are comfortable in Linux/HPC environments - Fluent English with excellent communication skills, able to explain technical simulation and ML concepts to both engineering and non-technical audiences - Self-directed, you don't need detailed roadmaps to make progress - Low-ego, collaborative, and eager to learn at the intersection of simulation and ML - Demonstrated success through industrial projects, academic work, or personal projects IT WOULD BE GREAT IF YOU - Have industrial or academic experience with simulation solvers (e.g. OpenFOAM, LS-DYNA, ANSYS, COMSOL, Abaqus, Fluent, STAR-CCM+, PowerFlow, NekRS, Tau/CODA, JAX-Fluids, or equivalent; Cadence/Synopsys/Siemens EDA or equivalent) - Have experience automating large-scale simulation campaigns on HPC clusters - Have contributed to a large open-source or industry codebase - Have publications in engineering or ML venues (AIAA, ASME, JFM, NeurIPS, ICLR, etc.) WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Paris; Amsterdam; Linz; Munich; London; Berlin Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role Mistral is looking for AI Scientists with deep ML expertise and hands-on engineering experience to expand what our agentic tools can do across the engineering lifecycle — CAE (CFD, FEA, etc.) and EDA/Semi. Working within the AI4Engineering Science team, your core work is building the pre and post-training data for Mistral's LLMs to reason about and execute real engineering tasks. Because Mistral trains its own frontier LLMs, the data and verifiers you design ship directly into models you can hold, a rare position, and the core of the job. Alongside this, you'll help shape the agent architectures and harness that let these models operate reliably inside multi-step engineering workflows, not just answer isolated questions. You'll work closely with domain experts across CAE and EDA or other domains to ground this work in how engineers actually work, and with the broader research team to translate that domain grounding into training signal and evaluation benchmarks that measure genuine task competence. This is early-stage work, and that's the point: you'd be joining at the foundation, shaping the data, verifiers, and agent scaffolding that decide whether these systems become reliable or stay demo-grade. There's no inherited playbook, you'll help define what good looks like, and your work will set the direction the team builds on rather than extend an existing one. What you will do - Design pretraining, SFT, and RL data for engineering tasks across CAD, CAE, and semiconductor/EDA - Define verifiers and evaluation criteria that capture what "correct" and "high-quality" actually mean for each engineering task, beyond surface-level plausibility - Design and improve agent architectures and harnesses: how models plan, call tools, recover from errors, and chain steps together across long-horizon engineering workflows - Build evaluation benchmarks and diagnostic tooling to identify where models fail on engineering tasks, and trace those failures back to gaps in data, reward design, or agent scaffolding - Collaborate with domain experts across CAE and EDA or other domains (and the science and solutions teams more broadly) to identify which engineering workflows are highest-value to target next - Contribute to Mistral's broader pre and post-training research, sharing findings and methodology across the science organization What we're looking for - Fluent English with excellent communication skills, able to explain technical ML and engineering concepts to both engineering and non-technical audiences - Deep, hands-on machine learning expertise, particularly LLM development - Demonstrated experience running, debugging, and validating real engineering workflows in at least one of CAD, CAE, semiconductor simulation, or EDA - You write clean, readable Python code and are comfortable in Linux/HPC environments - Self-directed, you don't need detailed roadmaps to make progress - Low-ego, collaborative, and eager to learn at the intersection of engineering and ML It would be great if you - Have experience building or fine-tuning agentic systems (tool use, multi-step planning, agent orchestration frameworks) - Have experience with reward modeling, RLHF/RLAIF/RLVR, or preference-based training - Have industrial or academic experience with CAE or EDA tools (e.g. SolidWorks, CATIA, Fluent, Abaqus, LS-DYNA, STAR-CCM+, Cadence/Synopsys/Siemens EDA tools) - Have contributed to a large open-source or industry codebase - Have publications in engineering and ML venues (NeurIPS, ICLR, JFM, AIAA, etc.) WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic runs one of the largest and fastest-growing infrastructure fleets in the industry, across multiple accelerator families, CPU families, clouds, neoclouds, and on-prem sites. Capacity Engineering owns the data, tooling, and systems that let Anthropic plan, measure, and maximize utilization of that fleet: we partner on supply deals, wire telemetry from day zero, own the canonical capacity data layer, and build the planning and enforcement tools every research and product team relies on. This role sits in the Planning pillar, on the Demand Planning team, and works daily with research engineering, pretraining, inference, compute supply, finance, and external vendors. You own the tranches. The job has two halves that feed each other. Upstream, you take the Demand Planning forecast and turn it into per-tranche requirements — shape, interconnect, region, supporting resources, date — and carry those into sourcing negotiations and data center build reviews so we contract for capacity we can actually use when we need it. Downstream, you own the integrated schedule and system of record for every tranche in flight — from contracted through reserved, ingested, in-cluster, healthy, and occupied — and you drive the owners of each hop to their dates. Every slip you see downstream becomes a contract-language fix, an automation, or a correction fed back to the forecast. What you'll do Turn the forecast into per-tranche requirements. Take the Demand Planning forecast plus direct input from research, pretraining, and inference planners, and convert it into concrete accelerator, interconnect, region, supporting-resource, and date requirements for each tranche. Represent those in sourcing negotiations and data center build reviews, including which contractual terms actually move delivery dates. Qualify tranches for deliverability before signature. The Capacity Planner signs fit-to-forecast; you sign whether the shape can land schedulable, healthy, and instrumented in that region on that date, with storage, egress, identity in place. Close the delivery loop. Track forecast-versus-delivered on shape, region, and timing for every tranche; publish the variance; and feed it back to Demand Planning and into the next contract. Own the bring-up system of record. Define the canonical contract-to-occupied state machine with explicit entry and exit criteria per stage, and make it a first-class object in the capacity data layer so every downstream tool sees in-flight capacity, not only what has landed. Run a portfolio of bring-ups in parallel — new cloud regions, on-prem sites, neocloud blocks — with one integrated schedule spanning provider milestones, cluster creation, network turn-up, storage readiness, health burn-in, and first-workload landing. Drive readiness automation: All capacity systems are fully integrated for all new capacity, from contracted through ingested, automated and scaled. Instrument and publish the numbers that matter — time-to-occupied and paid-idle dollars per tranche — with executive-level reporting on status, tradeoffs, and risk across the portfolio. What you bring Significant experience delivering large-scale infrastructure — cloud regions, accelerator clusters, HPC systems, or bare-metal fleets — at multi-region scale or ≥10k accelerators (or CPU/storage equivalent). Technical range from through cluster orchestration and node health, up to the telemetry and planning tables on top — enough to debug where they disagree rather than route it. SQL and enough Python to answer your own questions and build your own reporting. A degree in a technical field or an equivalent engineering track record. Preferred Reserved-capacity onboarding, private offers, or capacity commitments with cloud or neocloud providers. Enough demand-planning exposure to challenge a forecast, translate it into per-tranche requirements, and feed delivery variance back into it. Data center or colocation delivery: power and space planning, network turn-up, site acceptance, vendor management. Accelerator health and burn-in, collective-communications sanity testing, or fleet-health SLOs — and a rigorous definition of "healthy." Systems of record or lifecycle services for infrastructure assets. Onboarding a new hardware generation into an existing scheduler and observability stack. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: United Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus Workplace: remote Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job As a member of the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: multi-modal data curation and alignment, strengthening baselines, and identifying and resolving existing pre-training bottlenecks to push the limits of cross-modal AI performance. Responsibilities Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs. Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding. Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training. Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency. Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs. System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. 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). Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance. Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. 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: Europe Workplace: Remote Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. ABOUT THE ROLE Synthesia's long-term vision is to build the best human-interactive models: systems that don't just talk to people, but perceive and respond to them, reacting to a user's actions and emotions, not only their words. Today over 60,000 businesses rely on our platform, and the next leap in what we can offer them depends on models that combine text, audio, and video into a single real-time interactive experience. As a Staff Research Engineer, you'll join the Voice team within our 40+ person R&D department, but your scope will extend well beyond voice. You'll help define and drive that broader vision across teams, proposing ambitious research directions and taking direct ownership of the design and implementation of its most critical components. You'll work directly with our voice lead and collaborate tightly with our video teams and other senior members of the org. Concretely, you'll work on voice to voice models that produce text and voice simultaneously. Models that can reason, interrupt the user with back channeling and talk. Models that feel like you are having a natural conversation with, without the feeling of turn taking that is dominant in current speech to speech models. Your role would be to partner in defining a roadmap, implementing it and shipping the outcomes to product. What you'll do - Shape our roadmap to create new model capabilities and unlock new functionality for our customer base, on both short and long time horizons. - Propose novel multi-modal system architectures (especially text and voice). - Develop and evaluate streaming and conversational systems for low-latency, interactive voice-video synthesis. - Design solutions that reinforce emotional expressiveness and natural interaction. - Implement and bring designs to life, from pretraining through post-training. - Integrate and test novel architectures (neural codecs, diffusion, flow-matching) to enhance realism and responsiveness. - Define new evaluation metrics for conversational systems, including latency-aware and interaction-based measurements. - Track the latest research in audio-visual diffusion, autoregressive models, neural codecs, and multimodal LLMs. - Curate new datasets to complement existing data. - Lead post-training initiatives like DPO, fine-tuning, and distillation to bring models to shipping quality. - Ship models to production with optimised runtime to serve customers, and address their feedback thereafter. YOU'LL THRIVE IN THIS ROLE IF YOU HAVE - The ability to bring novel ideas and designs that advance the field of interactive multimodal systems. - Strong understanding of generative modelling, ideally applied to sequential or multimodal data. - Hands-on experience with large language models or similar transformer-based architectures. - High proficiency in PyTorch, including distributed training and model optimization. - A solid grasp of time-series modeling and tokenization, preferably in the context of audio, speech, or video. - A demonstrated ability to prototype quickly, test hypotheses, and iterate efficiently. - Proven experience training deep learning models end-to-end, from data preparation through evaluation. - Strong general software engineering skills, enabling contributions to a large, shared research infrastructure. PARTICULARLY RELEVANT EXPERIENCE - Having shipped a generative model into a live product used at meaningful scale, not just published or prototyped it. - Working on conversational or interactive systems where latency, responsiveness, and user experience were first-class constraints, not afterthoughts. - Working on LLMs with large scale trainings leadings to models with decent reasoning capabilities - Owning a research problem end to end: from architecture proposal through pretraining, post-training, and production deployment. - Collaborating across modalities or teams (e.g. audio and video, or research and product) to ship a unified system. BONUS POINTS FOR - Experience with real-time or streaming architectures. - Familiarity with state-of-the-art architectures in audio and speech generation, such as diffusion models, neural codecs, flow-matching models, or autoregressive decoders. - Excellence in one or more of the following modalities: voice, text, video. - Evidence of original research contributions, such as publications or open-source work at top-tier venues (e.g. NeurIPS, CVPR, ICML, ICLR, Interspeech).

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. OUR MISSION At Humanoid we strive to create the world's leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity. ABOUT THE ROLE As a Research Engineer on the World Models team, you will build action-conditioned generative models that predict how the world evolves around our robots — future video, proprioception, contacts, and outcomes — from past observations and actions. World models serve four purposes in our stack: a pretrained, physics-aware prior for our VLA policies; an engine for rare data collection, cross-platform transfer, and sim-to-real transfer; a testbed for policy evaluation and testing before hardware; and a future-prediction rollout engine that surfaces what our policies intend to do, for safety and planning. This is a hands-on individual contributor role: you will design architectures, run large training jobs, and validate your models against real fleet data from industrial deployments. WHAT YOU'LL DO - Design and train multimodal world models — video, state, action, and language — using diffusion-based and transformer architectures. - Build action-conditioned video prediction and dynamics models that stay physically consistent over long horizons, including contact-rich manipulation, and serve as pretrained priors for VLA policies. - Develop learned-simulator evaluation: score candidate policies offline, predict real-world success rates before deployment, and roll out policy futures to expose intended behaviour for safety review and planning. - Generate synthetic rollouts and counterfactual experience — including rare events, cross-platform transfer, and sim-to-real transfer — to augment policy training, and measure their effect on downstream task performance. - Establish fidelity metrics and calibration protocols that quantify where the world model can be trusted and where it diverges from reality. - Build data pipelines that turn fleet telemetry, teleoperation logs, and internet-scale video into training corpora for world models. - Run scaling and ablation studies on architecture, data mixture, and context length; communicate findings crisply. - Collaborate with pretraining, RL, and manipulation teams to integrate world models into policy training and evaluation loops. WHAT WE'RE LOOKING FOR - A track record of training large generative models — video, world, or multimodal — with shipped models or published artifacts to show for it. - Deep hands-on experience with modern generative architectures: diffusion models, autoregressive transformers, latent-variable models, or video prediction. - Experience with large-scale distributed training: streaming datasets, checkpointing and state management, debugging numerics and training instabilities. - Strong Python + PyTorch/JAX; you can profile kernels, optimize data loaders, and write maintainable research code. - Empirical rigor: you design careful evaluations, run honest baselines, and document experiments clearly. - Excitement about grounding generative models in physical reality rather than pixels alone. NICE TO HAVE - Experience with world models for robotics or autonomous driving (e.g., action-conditioned video models, learned simulators, model-based RL). - Familiarity with robotics simulators (Isaac Sim, MuJoCo) and sim-to-real considerations. - Experience using world models for policy evaluation or synthetic data generation at scale. - Publications at top-tier deep learning conferences (NeurIPS, ICML, ICLR, CoRL, CVPR) or equivalent open-source contributions. - Experience optimizing generative models for fast inference. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We're hiring a VLA Pre-training Engineer to join our Autonomy team based in London. In this role you will you will work on all aspects of training capable policies, be it pre-training of a base model on a diverse multi-embodiment corpus of trajectories, fine-tuning a policy to perform a specific task well, curating data collection processes or exploring productive ways to generate and use synthetic data. This is primarily a deep learning-focused role, so we are looking for experience solving real problems using modern neural networks, while experience in robotics isn’t strictly required. However if you don’t have such experience, be prepared that you’d need to familiarize yourself with a new domain quickly.   WHAT YOU'LL DO - Post-train policies via behaviour cloning and RL; own the full loop from data to deployment. - Partner with the Data Collection team to drive collecting new data: specify what good data looks like, identify failure modes, ensure diversity and coverage. - Work closely with external partners to ensure steady supply of high-quality pretraining-scale data. - Run pre-/mid-/post-training on VLA stack; explore new modalities and architecture changes. - Build and maintain continuous pipelines: ingest synthetic data and teleop logs, version them, apply weak‑supervision labelling, curate balanced datasets, and auto‑surface fresh failure cases into retraining. - Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‑time edge inference. WHAT WE'RE LOOKING FOR - 3+ years building deep‑learning systems (industry or research) with shipped models or published artifacts to show for it. - Deep hands‑on experience with at least one of: LLMs, VLMs, or image/video generative models — architecture, training, and inference. - Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies. - Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code. - Familiarity with modern software engineering practices. - You document experiments clearly and communicate trade‑offs crisply. NICE TO HAVE - Robotics or autonomous driving experience. - Experience applying RL to LLMs or robotics. - Experience with VLA (vision-language-action) models. - Proven productization of deep nets (latency/throughput constraints, telemetry, on‑device optimization). - Publications at top-tier deep learning conferences or equivalent open‑source contributions. - Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open source VLA frameworks. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: Paris; Palo Alto; London ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE As a Strategic Data & Licensing Partnerships Negotiator on the Strategic Data & Licensing Partnerships team, you will drive the acquisition of premium content and negotiate complex agreements to secure high-value data and content for AI training, RAG, and distribution. Your work will enable Mistral AI to access quality, relevant sources while building long-term relationships with publishers, universities, research institutions, and data providers. You will collaborate closely with cross-functional teams to align content sourcing with Mistral AI’s strategic interests, ensuring innovative and ethical use of data. This role is for a results-driven negotiator who thrives in high-stakes deal-making and understands the intersection of AI, academic content, and ethical data practices. WHAT YOU WILL DO - Build and manage a pipeline of high-quality content (STEM, academic, robotics, multimedia) while vetting providers for legal and business compliance. - Negotiate complex, multi-pronged agreements (licensing, revenue-sharing, co-development) with publishers, universities, and research institutions. - Develop long-term partnerships that promote fair compensation and sustainability for content creators and owners. - Collaborate with internal teams (Science, Product, Go To Market) to align procurement with their objectives and evaluate "make vs. buy" options. - Provide regular reports and analytics on procurement activities to support data-driven decision-making. - Design programs that foster ethical and scalable content sourcing, balancing internal development with external licensing. WHAT WE'RE LOOKING FOR - Proven track record negotiating and closing complex deals ($10M+), including licensing, revenue-sharing, or co-development agreements. - Deep understanding of AI training data ecosystems and the ability to translate technical needs into business terms. - Legal acumen in data acquisition and content licensing, including knowledge of global copyright laws. - Strong STEM background (degree in Science, Technology, Engineering, Mathematics, or related field) and passion for academic content. - Excellent communication and stakeholder management skills, with experience negotiating with C-level stakeholders. - Business acumen in market analysis and financial modeling (e.g., DCF analysis). - Fluency in English and French; additional languages (e.g., German) are a plus. - Existing network in publishing, academic, or research communities or experience with AI training data (pretraining, RAG, synthetic data). WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We're seeking an exceptional Research Engineer to join our Life Sciences team at Anthropic. Our team is organized around the north star goal of accelerating progress in the life sciences, from early discovery through translation, by an order of magnitude. Our team likes to think across the whole model stack. In this role, you'll combine your deep expertise in machine learning engineering to develop novel evaluation frameworks and training strategies that push the frontier of what AI can achieve in biology. You'll work at the intersection of cutting-edge AI and the biological sciences, developing rigorous methods to measure and improve model performance on complex scientific tasks. You'll collaborate closely with world-class researchers and engineers to build AI systems that can engage in all phases of research and development, while maintaining our commitment to safety and beneficial impact. Previous experience in life sciences is welcome, but not required for this role. Minimum Qualifications Demonstrated experience training and evaluating large language models Proficiency in Python and familiarity with modern ML development practices Experience building and managing data pipelines for large-scale datasets Comfortable navigating ambiguity and developing solutions in rapidly evolving research environments Strong written and verbal communication skills, with the ability to work independently while collaborating effectively across cross-functional teams Preferred Qualifications 8+ years of machine learning experience Prior work experience in AI and biology, including graduate studies (molecular biology, biochemistry, computational biology, or related fields) Experience working with large-scale biological datasets Published research or practical experience in scientific AI applications or long-horizon reasoning Background in reinforcement learning and/or pretraining Knowledge of containerization technologies (e.g., Docker, Kubernetes) and cloud deployment at scale Demonstrated ability to work across multiple domains, such as language modeling, systems engineering, and scientific computing Contributions to open-source scientific software or databases The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 — $500,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: 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 the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: multi-modal data curation and alignment, strengthening baselines, and identifying and resolving existing pre-training bottlenecks to push the limits of cross-modal AI performance. Responsibilities Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs. Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding. Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training. Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency. Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs. System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. 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). Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance. Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. 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 the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: multi-modal data curation and alignment, strengthening baselines, and identifying and resolving existing pre-training bottlenecks to push the limits of cross-modal AI performance. Responsibilities Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs. Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding. Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training. Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency. Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs. System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. 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). Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance. Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. 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 the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: multi-modal data curation and alignment, strengthening baselines, and identifying and resolving existing pre-training bottlenecks to push the limits of cross-modal AI performance. Responsibilities Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs. Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding. Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training. Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency. Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs. System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. 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). Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance. Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. 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: Madrid, 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 the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: multi-modal data curation and alignment, strengthening baselines, and identifying and resolving existing pre-training bottlenecks to push the limits of cross-modal AI performance. Responsibilities Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs. Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding. Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training. Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency. Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs. System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. 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). Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance. Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. 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 the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: multi-modal data curation and alignment, strengthening baselines, and identifying and resolving existing pre-training bottlenecks to push the limits of cross-modal AI performance. Responsibilities Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs. Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding. Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training. Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency. Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs. System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. 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). Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance. Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. 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 the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: multi-modal data curation and alignment, strengthening baselines, and identifying and resolving existing pre-training bottlenecks to push the limits of cross-modal AI performance. Responsibilities Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs. Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding. Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training. Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency. Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs. System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. 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). Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance. Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. 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 the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: multi-modal data curation and alignment, strengthening baselines, and identifying and resolving existing pre-training bottlenecks to push the limits of cross-modal AI performance. Responsibilities Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs. Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding. Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training. Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency. Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs. System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. 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). Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance. Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. 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: Toronto; Europe; London; New York Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Senior Member of Technical Staff specializing in web data for pre-training, you will play a pivotal role in developing the large scale web data pipeline that underpins Cohere’s advanced language models. In this role, you will work extensively with large-scale web corpora, transforming raw, noisy internet data into high-quality training data for pretraining. You will own key components of the data pipeline, including extraction, parsing, deduplication, and filtering. You will also analyze the composition and quality of web data, study its impact on downstream model performance, and collaborate closely with the broader data and evaluation teams to iterate on the training corpus. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role. (EST/EU) Key Responsibilities: - Maintain large-scale pipelines for processing web corpora. - Work on filtering and quality-scoring systems to identify high-value web documents. - Analyze web data composition across domains, languages and time periods. - Develop and maintain highly-performant deduplication pipelines. - Collaborate with cross-functional teams, including researchers and engineers, to ensure data pipelines meet the demands of cutting-edge language models. Qualifications: - Strong software engineering skills, with proficiency in Python and experience building data pipelines. - Familiarity with data processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools. - Experience working with large-scale web datasets. - Knowledge of data quality assessment techniques and experimentation with data mixtures. - A passion for bridging research and engineering to solve complex data-related challenges in AI model training. Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP). If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.