Staff Research Engineer in United States

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including: model architecture and MoE routing optimization decoding and inference-time algorithm improvements software/hardware co-design for GPU acceleration performance optimization without compromising model quality Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production. You may be a good fit

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization, working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role You will own and execute long-term talent strategies to identify, engage, and recruit many of the world’s leading and emerging AI researchers, research engineers, and technical scientists working at the frontier of machine learning. This is not a traditional execution-focused recruiting role. You will operate as a strategic partner to OpenAI’s research staff, helping define hiring priorities, shape search strategy, influence candidate evaluation, and guide hiring decisions that directly impact the direction and quality of our frontier-model research and fulfillment of our mission. In this role, you will: Partner directly with research and technical staff to define hiring priorities, shape search strategies, and anticipate future talent needs as technical roadmaps evolve. Proactively identify and cultivate exceptional AI/ML research talent across industry, academia, and emerging labs, often before formal hiring needs exist. Use market insights and candidate signals to influence hiring decisions, leveling, and compensation strategy for highly specialized research roles. Serve as a trusted advisor throughout candidate evaluation and closing — helping leaders calibrate for research excellence, long-term potential, and organizational fit. Collaborate closely with your sourcing partner to execute complex, high-impact searches in ambiguous or rapidly evolving technical domains. You might thrive in this role if you: Significant experience recruitin

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Staff Research Scientist, Physical AI for our AI Research team . You will build the next-generation training and learning platform for physical AI: models that perceive, reason about, and act within structured environments . This is a greenfield (0 to 1) effort at the intersection of representation learning, world models, and policy optimization. You will help define its technical direction from day one. AS A STAFF RESEARCH SCIENTIST YOU WILL: Design and build scalable training infrastructure for representation models (e.g., contrastive and self-supervised approaches like CLIP/SigLIP, DINO/MAE, and joint-embedding predictive architectures) Develop latent world models that learn environment dynamics through imagined rollouts, enabling model-based reasoning and planning (Dreamer-style, I-JEPA/V-JEPA families) Architect and implement action/policy model pipelines, including vision-language-action models and diffusion-based policy learning Build generative simulator frameworks that produce controllable, physically plausible future states (video world models in the spirit of Cosmos/Genie/Sora) Develop multimodal generative model capabilities that fuse visual, language, and structured inputs for downstream reasoning and decision-making Lead cross-team technical de

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. THE MISSION We are seeking a Staff Research Scientist to serve as a technical pillar within our AI research organization. You will not just execute on roadmaps—you will define them. At the intersection of autonomous agents and large language models (LLMs) , you will build the models and systems that turn enterprise data into self-directed, decision-making agents —shifting from passive data access to autonomous execution. Our team operates at the frontier of enterprise AI, delivering both state-of-the-art models and production systems , including: Arctic LLM : Enterprise foundation models optimized for performance and efficiency Arctic-Text2SQL : Post-trained reasoning models with frontier-level quality at a fraction of cost and latency Snowflake Intelligence : Brought research to production through agentic innovations in multi-step reasoning, Deep Research for structured and unstructured insights, and system optimization Arctic Inference : High-performance LLM serving stack (Shift Parallelism, SwiftKV), open-sourced and powering Snowflake Cortex Arctic Long-Context Training : Enables 1M+ token context training on a single H200 GPU Agent World Models (AWM) : RL training across 1,000+ synthetic environments for tool-using agents We focus on core challenges such as reliable re

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. We are the Data Foundation & AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment, feature management,

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake's Data Engineering organization builds the platform that ingests, transforms, and stores data for modern lakehouse architectures — powering billions of queries, DML, and DDL operations with industry-leading price-performance. We lead the industry's shift to open data lakes through our work on Iceberg and Polaris, and we deliver capabilities like Snowpark, Dynamic Tables, cross-region replication, time travel, and zero-copy cloning at enterprise scale. We are investing in a new line of applied research — building toward verified data infrastructure and trustworthy data systems — that brings formal methods, automated reasoning, and modern AI techniques to bear on the hardest problems in our distributed systems and developer tooling. The goal is to improve correctness, reliability, and engineering velocity at a scale very few platforms operate at. We're hiring at both the Staff and Principal level; we'll calibrate the offer to the candidate's experience and scope of impact. What you'll do Lead research projects that apply formal methods, program analysis, automated reasoning, and AI-driven techniques (including code generation and modeling) to real problems in our cloud data platform. Translate research ideas into prototypes, then into shipped capabilities that move

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization—working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role We are looking for a highly strategic recruiter to work closely with the Head of Research Recruiting on a small set of unusually important, high-touch searches and candidate relationships. This role will focus on exceptional talent who does not move through a standard recruiting process: highly visible researchers, technical leaders, operators, and other special-interest candidates where timing, discretion, market intelligence, and tailored engagement matter as much as process execution. This is not a conventional req-based recruiting role. You will help identify where the market is moving, develop intelligence on top talent and competitor activity, translate that intelligence into action, and orchestrate bespoke recruiting strategies for candidates who require a more nuanced path into OpenAI. You should be able to translate these signals and states into clear, actionable advice for leaders and then make it happen. In this role, you will: Partner directly with the Head of Research Recruiting and research leadership team to define priority talent targets and shape bespoke engagement strategies. Build and maintain deep market intelligence across frontier AI, research, engineering, and adjacent talent ecosystems, including competitor movement, candidate motivations, and relationship context. Proactively identify, map, and cultivate exceptional high-profile talent before there is a formal or standard hiring process attached. Translate weak signa

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity As a Member of Technical Staff on AI Infrastructure, you will build and maintain the foundational systems and distributed infrastructure that power AI model post training, inference, and data pipelines. You will collaborate with engineering and research teams to ensure performance, scalability, and reliability of critical AI systems. What You’ll Do Design and implement large-scale, distributed AI infrastructure and services Optimize performance for GPU/xPU accelerators and cloud environments Build tools for observability, reliability, and scaling of AI workloads Partner with cross-functional teams to define AI infrastructure requirements and roadmap Contribute to architectural design and system longevity About You Have experience with GenAI infrastructure systems, distributed systems, cloud computing, and high-performance infrastructure Are proficient in programming languages like Python, Go, or similar Understand scaling challenges specific to AI workloads and accelerators Thrive in fast-paced, collaborative engineering environments The reasonably estimated base salary for this role ranges from $256,000.00 to $276,

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 For years, avatars have been something you watch. You write a script, we render a video, someone presses play. That model has taken AI video a long way but it has a ceiling. A video can't answer a question. It can't read the room. It can't role-play a tough conversation and adapt when you push back. We're changing that. Interactive Avatars listen, talk, and respond in real time; inside your product, your website, or your internal tools. You bring the logic and the language model; we power the avatar layer: the speech, the expression, the listening, the sense that there's someone actually there. It's early. Interactive Avatars is in closed beta today, and the teams building on it are pushing it into places we didn't expect - AI sales reps, always-on support agents, interactive trainers, onboarding guides. We're hiring a Product Manager to own it and take it from beta to a platform that thousands of developers build on. This is a role with real scope. You'll help define what a real-time avatar API should be, the surface developers integrate against, the experience end users feel, and the commercial model that makes it a business. You'll work directly with the engineering and research teams building

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . At Pinterest Labs , you'll work on tackling new challenges in machine learning and multi-modal large language models along with a world-class team of research scientists, and machine learning engineers. You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: natural language processing (NLP) and reasoning capability, computer vision for multi-modality, graph neural network, inclusive and responsible AI, reinforcement learning, user modeling, and recommender systems. What you’ll do: Contribute to cutting-edge research in machine learning and LLM that can be applied to Pinterest problems, especially search agent, recommendation agent, reason and planning agent Collect, analyze, and synthesize findings from data

We’re looking for a Staff Software Engineer to help shape AI governance for developer tooling at Coder. This role sits on our AI Governance team, which builds and maintains two enterprise-grade components of Coder's AI governance stack. AI Gateway is a centralized LLM gateway that sits between coding agents and providers such as OpenAI or Anthropic, providing organizations with audit trails, token tracking, cost control, and centralized authentication. Agent Firewall wraps those agents with default-deny network policies, controlling which domains and methods they can reach inside workspaces. This team works across the full stack - from Go backend and React frontend to integrating with LLM provider APIs. Day to day, you'll be shipping features, hardening security boundaries, collaborating with enterprise customers on real-world policy needs, and contributing to Coder's open-source ecosystem. What you'll do here Design and build product features that push the standard for remote development in self-hosted environments Create and improve upon popular open source projects that integrate with VS Code, JetBrains, and other developer tools Champion best practices to both internal team members and external contributors Collaborate with Product and Design teams at Coder, as well as with partners like JetBrains, to execute key product integrations Document the design, implementation, and operations of systems for knowledge sharing within the team Work alongside Customer Success teams to support Coder’s enterprise user base Work with cutting-edge AI technologies to create seamless, painless developer experiences Rapidly iterate from prototype to implementation in a highly adaptive, reactive team environment What we're looking for 8+ years of full-stack experience writing code in a professional setting, with 1+ year(s) writing Go (ideally in current or most recent position) Proficiency in building distributed systems in Go Excellent verbal and written communication skills Excep

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.