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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. THE OPPORTUNITY At Synthesia we really care about video generation, especially about human centric avatar video generation. This led us to release models such as EXPRESS-Video https://synthesiaresearch.github.io/express-video/, and soon our latest video model - these are the best avatar video models in the world, and we are committed to continuing and double down our efforts in leading that area. Our goal is to get to human centric video models that can generate arbitrary long videos at high resolution with arbitrary actions and events. That means continuously training large generative video models from scratch with the proprietary data pipelines and compute infrastructure to support it at scale. We are looking for a technical leader who owns the full stack end-to-end, someone who bridges pre-training and post-training, sets long-term direction alongside research leadership, and is personally present at the hardest parts of the work. If building foundation model capability from the ground up at a company genuinely committed to leading the field sounds like the right next challenge, this role was written for you. ABOUT THE ROLE Synthesia's video generation capability is core to everything we ship. It involves roughly 15 people working daily across pre-training and post-training stages, and the complexity of coordinating across those stages, at the scale of compute and data we now operate, requires a different kind of technical leadership. We're looking for a Principal Research Engineer (L7) to own the full technical stack for offline video generation. This is a senior individual contributor position with outsized scope and influence. You'll partner directly with research leadership and team leads to define long-term strategy, resolve the hardest cross-cutting technical problems, and raise the bar for how quickly research reaches product. The person we're looking for has trained large generative models from scratch, not supervised it from a distance, but done it, debugged it, and shipped it. More than that, they're driven by a genuine ambition to push what's possible in video generation, and they care deeply about seeing that work land in product and reach users. What you'll do - Own the end-to-end technical direction for offline video generation, spanning pre-training and post-training, resolving the artificial boundary between those two stages in service of shipping better models faster. - Partner with research leadership and team leads to define a unified long-term roadmap, broken into achievable objectives, and drive execution against it. - Identify the most critical technical gaps across the video generation pipeline and jump in to unblock them, whether that means architectural decisions, training stability, post-training alignment, or cross-team coordination. - Increase the velocity at which research ships to product: accelerate problem-solving, improve research-to-production handoffs, and increase visibility of research output in partnership with PMs. - Coach and elevate more junior researchers and engineers toward senior technical thinking and execution. - Help shape team structure and refine processes to enable high-velocity, cohesive execution across research. You'll thrive in this role if you have - A proven track record training large-scale video generation models from scratch, across multiple nodes, at the scale of millions of hours of data. - Deep experience with post-training techniques at scale: RLHF, GRPO, DPO, and the judgment to know when and how to apply them. - A proven track record data quality and you are not reluctant to question it. - The ability to think strategically about multi-year research direction and execute hands-on at the frontier of what the team is building. - Strong cross-functional influence: you shape how teams work together without needing positional authority to do it. - A leadership style grounded in technical involvement. You lead by example, inspire through craft, and communicate with clarity. - Genuine hunger to unlock new capabilities and an obsession with shipping. You're not satisfied by research that stays in a notebook. You want it in the hands of users. Particularly relevant experience - Having owned a major model generation or capability jump end-to-end, from training runs through to product deployment. - Working across both pre-training and post-training stages on the same model family, with direct accountability for the outcomes of both. - Experience operating at scale: large distributed training runs, significant compute budgets, and multi-million hour data pipelines. - Applying alignment and fine-tuning techniques in a video or multimodal context, not just text. - Experience with human feedback pipelines applied to generative video or audio. - Leading or significantly influencing the technical direction of a research team while remaining hands-on. Dealbreakers We will not be a good fit if you prefer to lead without staying technically involved, or if clear and direct communication across research and product isn't one of your strengths. This role requires presence at the frontier of the work, not above it. And if shipping doesn't excite you as much as the research itself, this probably isn't the right role.

Location: United Kindom, United Kingdom; Buenos Aires, Argentina; Bogotá, Colombia; Sao Paulo, Brazil; Montevideo, Uruguay; Bangalore, India; Chittagong, Bangladesh; Karachi, Pakistan; Tokyo, Japan; Hanoi, Vietnam; Taipei, Taiwan; Bangkok, Thailand; London, United Kingdom; Lugano, Switzerland; Barcelona, Spain; Dubai, United Arab Emirates; Sofia, Bulgaria; Prague, Czechia; Belgrade, Serbia; Copenhagen, Denmark; Tallinn, Estonia; Athens, Greece; Tbilisi, Georgia; Budapest, Hungary; Dublin, Ireland; Sliema, Malta; Oslo, Norway; Amsterdam, Netherlands; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Stockholm, Sweden; Brussels, Belgium; Tel Aviv, Israel; Istambul, Türkiye; Nicosia, Cyprus Workplace: remote Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job As a member of the AI model team, you will drive innovation in post-training methodologies, with a special focus on agentic behaviors and tool use. Your work will refine pre-trained models so that they not only deliver enhanced intelligence and domain specific capabilities, but also learn to reason, plan, and autonomously invoke external tools to solve real world, multi step tasks and applications on edge devices (i.e., smartphones). You will work on a wide spectrum of systems, ranging from streamlined, resource efficient agents that run on limited hardware to complex multi modal architectures integrating text, images, and audio, all optimized for tool augmented decision making. We expect you to have deep expertise in large language model architectures and substantial experience in post-training for agentic workflows, including tool use fine tuning, function calling, and reinforcement learning from feedback on multi turn interactions. You will adopt a hands-on, research driven approach to developing, testing, and implementing new post-training algorithms that unlock goal directed behavior, self correction, and reliable tool invocation. Your responsibilities include curating agentic training data (e.g., trajectories of tool use, reasoning chains, environment interactions), strengthening baseline performance, and identifying as well as resolving bottlenecks in post-training for tool augmented agents to achieve SOTA model quality. The goal is to build models that do not just know but also act, use tools, and adapt, pushing the limits of what agentic AI can achieve. Responsibilities Conduct end-to-end research and engineering initiatives to advance post-training of agentic and tool-use models to achieve SOTA results. Drive broad, cross-cutting model improvements, including factuality, instruction adherence, tool/function use, multi-agent coordination, and reasoning calibration. Design and enhance large-scale post-training systems, including data pipelines, training workflows, evaluation frameworks, and benchmark infrastructure. Develop rigorous evaluation suites and diagnostic tools to assess model readiness for deployment. Strengthen feedback loops from real-world product usage, incorporating both explicit and implicit user signals into post-training. Collaborate with tooling, product, and training teams to improve the usefulness, reliability, and agentic capabilities of frontier models. Closely liaise with research, engineering and cross-functional teams to determine which integrations are production-ready for inclusion in major model releases. Degree in Computer Science, Machine Learning, or a related field; advanced degree (MS/PhD) preferred with a strong publication record in top-tier AI conferences. Experience with multimodal post-training workflows and data pipelines, particularly for agentic systems and tool use. Hands-on experience applying post-training at scale using distributed training frameworks (e.g., multi-node GPU environments). Demonstrated experience improving model capabilities in areas such as reasoning, tool use, and multi-agent coordination that achieve SOTA results. Proven track record of open-source contributions related to agentic systems or tool use (code, datasets, or models) on platforms such as GitHub or Hugging Face. Publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, ECCV). Important information for candidates Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles: Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/ Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website. Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms. Double-check email addresses. All communication from us will come from emails ending in @ tether.to or @ tether.io We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately. When in doubt, feel free to reach out through our official website.

Location: Europe ABOUT CANTINA Cantina is a new social platform founded by Sean Parker with the most advanced AI character creator. Our bots are lifelike, social creatures that can interact wherever people are online—across voice, video, and text. Create yourself, imagine someone new, or choose from thousands of characters to share infinitely scalable, personalized content and seamless group chat. If you’re excited about how AI can shape creativity and social interaction, come help us build what’s next. ABOUT THE ROLE: We’re looking for a Research / ML Engineer to join our Speech Team to build state-of-the-art speech systems end-to-end—from data specs through production inference. You’ll drive the model ↔ data ↔ eval flywheel for TTS and adjacent tasks (voice cloning, controllable TTS, voice conversion and more), partnering closely with research, data, and infra to ship fast, reliable, and cost-aware models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. WHAT YOU’LL DO: - Model Building: Architect, implement, pre-train, fine-tune, and post-train/alignment (e.g., GRPO/DPO) for large-scale speech models. - Project Leadership: Independently lead small research projects while collaborating on larger team initiatives. - Experimental Design: Design, run, and analyze scientific experiments to advance our understanding of the models. - Tool Development: Develop and improve dev tooling to enhance team productivity. - Full-Stack Contribution: Contribute to the entire stack, from low-level optimizations to high-level model design. - Data Ownership: Define data requirements and collaborate on acquisition, curation, augmentation, labeling quality, and synthetic data strategies. - Rigorous Evaluation: Design automated objective/subjective evaluations—listening tests, SV/WER/ASR-based metrics, robustness & bias checks, and red-team studies. - Pipeline Delivery: Harden the training → evaluation → inference pipeline; profile latency, memory, and cost; and meet production SLAs with robust monitoring and rollback. - GPU Scaling: Partner with infrastructure to run distributed training/inference on cloud fleets and productionize models with reliability and observability. - Safety & Responsibility: Contribute to safety/consent guardrails and to misuse/abuse mitigation for responsible speech technology. WHAT YOU’LL BRING: - Exceptional research/development experience with large scale audio models (>3B models and >500k hours data). - Exceptional understanding and hands-on experience with transformer architectures and/or diffusion models (inc. distillation and streaming) and/or audio language modelling. - Strong experience with multi-node and multi-gpu distributed model training. - Strong software engineering skills with a proven track record of building complex systems - Strong with PyTorch and performance work (profiling, CUDA/Triton/C++ as needed) and writing reliable production quality code. - Shipped large scale speech/audio models to production. - Background in working with large-scale ML data. - Ability to iterate on data,, and triangulate quality using subjective and objective signals. - Notable publications and/or open source contributions in speech/audio/ML. - Experience with voice-cloning, speech-control, voice-generation. PREFERRED EXPERIENCE: - Shipped large scale speech/audio models (TTS/VC/ASR) to production. - Work on large-scale ML systems. - Experience with audio language modelling, transformer architectures. - Experience with voice-cloning, speech-control, voice-generation. - Background in processing large-scale ML data. - Publications or notable open-source in speech/audio/ML. COMPENSATION: When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.   BENEFITS FOR U.S.-BASED ROLES: - Competitive salary and generous company equity - Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina - 42 days of paid time off, including: - 15 PTO days - 10 sick days - 15 company holidays - 2 floating holidays - Generous parental leave & fertility support - 401(k) retirement savings plan - Lifestyle spending account – $500/month to use however you’d like - Complimentary lunch and snacks for in-office employees - One Medical membership, and more!

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic's research organization works across the full model development lifecycle, from pre-training and post-training to alignment, interpretability, and safety, each operating at the frontier of AI development. As a Technical Program Manager for Research, you'll define and build the programs that research teams need most. You'll move across research areas like compute, evals, RL environments, and emerging research initiatives, going deep enough in each to understand how researchers work and what they need. You'll identify where the biggest opportunities for impact lie, find the highest-leverage gaps, and build the programs, processes, and tooling that allow researchers to focus on research. This is a 0-to-1 role: you'll explore new domains as priorities shift, determine what each one needs, and create lasting impact where none existed before. Note: This role may require responding to incidents on short-notice, including on weekends. Responsibilities Embed deeply within a research domain to understand the technical landscape, build trust with researchers and technical leaders, and identify the highest-leverage problems to solve, knowing the surface area will shift over time as research priorities evolve Move fluidly across research areas like compute, evals, RL environments, and emerging research initiatives, picking up new domains quickly and getting to depth fast Drive end-to-end execution of complex, ambiguous research initiatives spanning multiple teams, often without established playbooks or precedent Establish processes and frameworks that bring structure to unstructured research environments without slowing researchers down Lead efforts like large-scale compute resource planning, including allocation, efficiency, and prioritization across research and production workstreams Drive eval readiness for model launches by standardizing results, shaping eval plans early, improving tooling, and ensuring honest, transparent reporting across research, product, and marketing Own execution and operational health of RL environments across major training runs, coordinating cross-team trade-offs and feeding insights back into roadmap planning Equip research leadership to make decisions quickly by going deep on technical tradeoffs and presenting clear, actionable recommendations Act as the connective tissue between research, engineering, and product teams to reduce chaos and accelerate execution You May Be a Good Fit If You Have a background in ML research or engineering with several years of experience building technical programs from scratch, ideally with hands-on exposure to training, evaluation, or large-scale distributed systems Are a fast learner who can ramp on unfamiliar technical domains quickly and contribute meaningfully to discussions with researchers Are resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in fast-moving research environments Have a track record of operational ownership of complex technical systems, including monitoring, incident response, and performance optimization Can reason about technical tradeoffs at depth across model architecture, training infrastructure, evals, or compute efficiency, and translate them into clear decisions for leadership Have excellent stakeholder management skill and the ability to influence senior technical staff through competence and consistent delivery Are comfortable with high-stakes environments where decisions impact compute spend, model training timelines, and launch outcomes Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems Are excited to redefine what technical program management looks like at the frontier of AI research 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: $365,000 — $435,000 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: Athens Workplace: Hybrid About the company: KIEFER is building Greece's integrated AI ecosystem. From renewable energy infrastructure and AI systems to robotics and enterprise applications, we connect the technologies that power Europe's intelligent future. Founded in 2014, KIEFER has delivered 600MW+ of energy projects and is now developing sovereign AI infrastructure, enterprise AI products and physical AI systems for Greece and Southeast Europe. About the role: We are looking for an ML Team Lead to join Kiefer Tech and lead our ML Engineering team. In this role, you will lead the development and continuous improvement of Sophea AI, our Greek-focused Large Language Model. You will work across LLM training, fine-tuning, ASR, inference optimization, model validation, and production-grade ML systems. Beyond the model itself, you will help shape the ML Engineering function at Kiefer Tech: define clear ownership, strengthen team workflows, raise technical standards, and ensure complex ML initiatives are delivered with accountability, clarity, and strong execution. What you will do: - Lead the ML Engineering team working on Sophea AI and set a clear technical direction for its development - Own delivery across core ML workstreams, including LLM training, fine-tuning, ASR, inference optimization, model validation, and production-grade ML systems - Build a stronger operating model for the ML function: improve workflows, clarify ownership, strengthen decision-making, and remove execution blockers - Turn the ML roadmap into clear priorities, accountable workstreams, and measurable outcomes aligned with product and business goals - Mentor ML engineers, develop team capabilities, and bring stronger engineering practices, tools, and research-driven approaches into the team’s daily work What you will need: - Proven experience leading ML Engineering teams or complex ML workstreams in high-performance, fast-moving environments - Deep technical background in LLMs, ASR, and production-grade ML systems, including pre-training, training from scratch, fine-tuning, reinforcement learning, model validation, and performance improvement - Strong understanding of inference optimization, model quantization, and serving frameworks such as vLLM, SGLang, NVIDIA Triton, NVIDIA Dynamo, or similar tools - Ability to bring structure into ambiguous environments: clarify ownership, improve workflows, and drive execution across several ML workstreams - High autonomy, strong communication skills, and the ability to follow current AI research and translate relevant tools, methods, and trends into team practice Nice to have: - Experience with MLOps infrastructure, model serving pipelines, GPU workload management, and experiment tracking - Contributions to open-source ML projects or published research in AI/ML - Familiarity with real-time inference systems or event-driven ML architectures What is there for you: - Compensation: highly competitive package aligned with AI talent benchmarks across Europe and the US - Ownership: high-impact leadership role with real influence on the ML Engineering function at Kiefer Tech - Work format: remote work option, with relocation support available for candidates open to working from our Athens office - AI-native environment: real challenges across LLMs, ASR, GPU workloads, and advanced AI product development - NVIDIA ecosystem: access to related conferences, certifications, internal knowledge sharing, and advanced AI infrastructure through Kiefer’s strategic collaboration - Culture: engineering-first, high autonomy, low bureaucracy, and space to shape meaningful AI products

Location: London, UK 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 RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run. Responsibilities Build and improve the RL training infrastructure that researchers depend on day-to-day Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster Own the reliability and performance of research runs end-to-end Contribute to design decisions that shape how Anthropic does RL at scale You may be a good fit if you Have strong software engineering fundamentals and a track record of building performant, reliable systems Have worked on ML infrastructure, distributed systems, or research tooling Care about enabling other people's work and find leverage through platforms rather than individual experiments Are comfortable operating across the stack, from low-level performance work to RL algorithms Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego Strong candidates may also have Experience with large-scale distributed training (RL, pre-training, or post-training) Familiarity with JAX, PyTorch, or similar ML frameworks A track record of operating at the edge of research and infra in a fast-moving environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £370,000 — £630,000 GBP 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: Remote-Friendly (Travel-Required) | 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 RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run. Responsibilities Build and improve the RL training infrastructure that researchers depend on day-to-day Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster Own the reliability and performance of research runs end-to-end Contribute to design decisions that shape how Anthropic does RL at scale You may be a good fit if you Have strong software engineering fundamentals and a track record of building performant, reliable systems Have worked on ML infrastructure, distributed systems, or research tooling Care about enabling other people's work and find leverage through platforms rather than individual experiments Are comfortable operating across the stack, from low-level performance work to RL algorithms Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego Strong candidates may also have Experience with large-scale distributed training (RL, pre-training, or post-training) Familiarity with JAX, PyTorch, or similar ML frameworks A track record of operating at the edge of research and infra in a fast-moving environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. 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: Remote Workplace: Remote We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE *Open to hiring remote across the US — preferable to have someone near an office in NYC or San Francisco. This is a rare PM role with true vertical ownership across the full product lifecycle; from early-stage research and pre-training through to post-training and UX buildout through to GTM strategy and pricing - giving the right person a GM-like mandate to drive product decisions end-to-end in a way that's unique for a company of our scale. We’re looking for a passionate Product Manager to help us develop cutting-edge AI tools. This role is for someone who has a combination of strong technical or ML background and experience in product management. You have the ability to take the state-of-the-art AI systems our research team builds and turn them into impactful tools for our customers. You’ll deeply understand what users want, what’s possible to build, and what’s strategic for our business. You’ll be a bridge between our users and our internal teams so we ship products that have the most value for Runway’s creators. This role is a fundamental and critical part of the team for a market-defining company in its early stages. WHAT YOU’LL DO - Work alongside our research team to define new AI applications that solve customer needs and drive business value - Collaborate closely with engineering and design to productize research and continuously improve existing tools - Define and analyze metrics, talk with users weekly, and conduct A/B tests to discover use cases, validate pain points, and prioritize features WHAT YOU’LL NEED - 1+ years of direct experience with SQL, python, code generation tools, and version control best practices - 4+ years of product management experience - Familiarity with the current state-of-the-art ML capabilities and ML products - Experience working with fast-moving teams and building products from scratch - Passion for seeing research through from initial conception to ultimate application - Excellent written and verbal communication skills Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

Location: United Kindom, United Kingdom; Amsterdam, Netherlands; Buenos Aires, Argentina; Athens, Greece; Bangalore, India; Chittagong, Bangladesh; Dhaka, Bangladesh; Barcelona, Spain; Belize; Bogotá, Colombia; La Paz, Bolivia, Plurinational State of; Brasilia, Brazil; Brussels, Belgium; Cairo, Egypt; Chiasso, Switzerland; Santiago de Chile, Chile; Como, Italy; San Jose, Costa Rica; Zagreb, Croatia; Prague, Czechia; Delhi, India; Copenhagen, Denmark; Santo Domingo, Dominican Republic; Dubai, United Arab Emirates; Dublin, Ireland; Quito, Ecuador; Addis Ababa, Ethiopia; Helsinki, Finland; Accra, Ghana; Guatemala; Jakarta, Indonesia; Tel Aviv, Israel; Madrid, Spain; Lugano, Switzerland; Johor Bahru, Malaysia; Kuala Lumpur, Malaysia; Sliema, Malta; Manila, Philippines; Medellin, Colombia; Mexico City, Mexico; Milano, Italy; Montevideo, Uruguay; Nairobi, Kenya; Kathmandu, Nepal; Auckland, New Zealand; Wellington, New Zealand; Managua, Nicaragua; Lagos, Nigeria; Oslo, Norway; Islamabad, Pakistan; Panamá, Panama; Lima, Peru; Warsaw, Poland; Lisbon, Portugal; Rabat, Morocco; Rio de Janeiro, Brazil; Bucharest, Romania; Rome, Italy; San Salvador, El Salvador; Sao Paulo, Brazil; Riyadh, Saudi Arabia; Edinburgh, United Kingdom; Belgrade, Serbia; Sofia, Bulgaria; Colombo, Sri Lanka; Stockholm, Sweden; Berne, Switzerland; Geneve, Switzerland; Taipei, Taiwan; Tallinn, Estonia; Tbilisi, Georgia; Bangkok, Thailand; Abu Dhabi, United Arab Emirates; Hanoi, Vietnam; Yerevan, Armenia 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 We are looking for talented individuals to join us for an internship in 2025/2026. MSc/PhD Internships at Tether aim to provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. In our team, you will have the opportunity to participate in the development of the state-of-the-art (SOTA) foundation models, and will also be responsible for optimizing our distributed model training framework continuously. PhD internships at Tether provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis. We encourage you to apply early. Please state your availability clearly in your resume (Start date, End date). Responsibilities Research and develop state-of-the-art LLM and/or video or multimodality models to accelerate open-source progress in the domains. Implement the application of large models in our business scenarios, like pre-training, supervised fine-tuning, post-training, inference etc. Continuously optimize the training framework to better adapt to the training of large models on thousands of multi-node GPUs. In this role, you’ll have the opportunity to advance the development of open-source LLM, vision and/or multimodal foundation models and products. You will have the opportunity to collaborate with broader teams across Tether. MSc/PhD candidate in computer science or a related technical discipline Related Research Experience at least one of the following areas: LLM, computer vision, multimodality Be proficient with PyTorch deep learning framework and libraries Have excellent analytical and problem-solving skills, logical thinking skills, communication and collaboration skills Publications in the top AI conferences (e.g., ACL, NIPS, ICML, ICLR, CVPR, ICCV, ECCV, TPAMI, IJCV, etc.) is a nice to have. 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; New York; Paris; Toronto; Montreal Workplace: Hybrid 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 Performance Engineer in the Pre-Training team you will be responsible for optimizing the performance of our advanced language models and systems. Their primary focus is on improving key model training metrics, such as training throughput, ensuring high accelerator utilization. The team combines expertise in software engineering, machine learning, and low-level kernel design and development to design robust systems and enhance model performance. You will work on identifying and removing performance bottlenecks, develop cutting-edge training and profiling tools to help Cohere's mission of providing efficient and reliable language understanding and generation capabilities and drive innovation in the field of natural language processing. Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote-friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration. Key Responsibilities: - Design and write high-performant and scalable software for training.  - Understand architectural modifications and design choices and their effects on training throughput and quality. - Write low-level CUDA, triton kernels to squeeze every last bit of performance from our accelerators. - Research, implement, and experiment with ideas on our supercompute and data infrastructure. - Learn from and work with the best researchers in the field. Qualifications: - Extremely strong software engineering skills. - Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR. - Experience writing kernels for GPUs using CUDA, triton, etc - Experience using large-scale distributed training strategies. - Familiarity with autoregressive sequence models, such as Transformers. Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP). 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.