Staff Engineer Jobs

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 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 . The Ads & Monetization organization sits at the heart of Pinterest’s business, where machine learning, AI, creatives, attribution, reach, and marketplace come together to create value for advertisers and relevant, inspiring experiences for Pinners. Pinterest is at an inflection point. Hundreds of millions of users come to the platform with active commercial intent — making Pinterest uniquely positioned to influence the full purchase journey from inspiration to action. We are building a path of non-linear growth with emerging surfaces, expanding international markets, and foundational investments in relevance, advertiser return on ads spend, measurement, and creative quality. Unlocking that path requires disciplined, technically sophisticated execution across a collaborative, multi-team environment spanning technology, strategy, go-to-

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. In this position, you will be joining a brilliant team to collaborate with Micron’s various design and verification teams all over the world, support the efforts of design verification flow development, optimization, and implementation and work with cross-functional team to assure the best cost, quality, reliability, time-to-market, and customer satisfaction As Memory Design Group CAD Engineer at Micron Technology, Inc., you will be working in a collaborative, production support role evaluating, developing enhancing and debugging both in-house and commercial Electronic Design Automation (EDA) tools and flows for the physical layout and design of CMOS integrated circuits. You will work closely with the Design, Layout teams, supporting their use of electronic design automation tools and methodologies to increase design and layout productivity and work efficiency. Responsibilities : Develop tools, flows, and methodologies to increase the productivity and reliability of our Memory designs Integrate commercial EDA (Electronic Design Automation) tools into design flows Provide training, documentation, and support to end users on new tools and method. Work closely with design, layout, verification and process teams. Undertake independent research and development of ne

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’re looking for someone to oversee internal AI use for non-coding. In this role, you’ll partner with our go-to-market, operations, and technical teams to build and deploy AI functionality to increase efficiency and outcomes. Responsibilities Identify and validate high-impact AI opportunities for internal teams, like Sales, GTM, Finance, HR, etc and build solutions to increase efficiency and outcomes. Train teams to use these tools, monitor usage, and improve as opportunities present themselves. This role will work closely with our CEO Qualifications : 5+ years of product management or engineering experience, including >1 year building AI tools Experience working with GTM teams is a plus [nice to have] Founder experience Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring somethin

The opportunity Datadog’s Infrastructure products help engineers understand and operate the systems their applications depend on. Our customers work in complex environments like Kubernetes and serverless, where infrastructure changes constantly, information is dense, and decisions about reliability, performance, and cost are closely connected. We’re looking for a Staff Product Designer to join Modern Compute, with an initial focus on Containers Autoscaling. Autoscaling helps engineering teams make better decisions about how their applications and infrastructure use resources. Designing these experiences requires making deeply technical systems understandable, helping customers act with confidence, and fitting into the tools and workflows they already use. The team is rethinking how workload and cluster autoscaling come together as a more coherent product experience. This includes how customers get started, understand recommendations, evaluate value, and safely apply changes across their environments. The work also connects to other parts of Datadog, including observability, Cloud Cost Management, permissions, and AI-assisted workflows. As a Staff Product Designer, you will help define that direction and lead the work from early problem framing through shipped product. You will partner closely with product and engineering, bring a high level of interaction and visual craft to complex workflows, and help raise the quality of design across Modern Compute. At Datadog, we place value in our office culture, the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to help our Datadogs find a work-life rhythm that works for them. What you’ll do Lead end-to-end product design for Modern Compute, initially focused on our Autoscaling product. Help define the product direction for an area that is still evolving, from early framing and exploration through detailed design and delivery. Design clear, trustwort

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As a Smart Manufacturing Product Owner at Micron Technology, Inc., you will be responsible to enable innovation and new frontier technology for Smart manufacturing to define, drive and deliver end to end smart manufacturing solution, coordinated across functions of the business. The team will look into applying industry-leading the best methodologies in automation, AI and machine learning to improve Micron’s product development, business and administrative processes across the company. You are joining a team where 'we' matter and hold high standards to achieve perfection. Key Responsibilities Lead the development and implementation of AI-driven Smart Manufacturing solutions to improve product yield, quality, test coverage, and system-level performance across Micron's semiconductor operations. Partner with Test Solutions Engineering, Product Engineering, Global Quality, and multi-functional collaborators to find opportunities and drive digital transformation initiatives. Collaborate with Data Scientists, Machine Learning Engineers, Solution Architects, and Data Engineers to define requirements, prioritize solutions, and deliver end-to-end projects. Translate business needs into detailed business requirements, user stories, acceptance criteria, and data requirements while ensuring alignment with enterprise standards and governance. Develop arguments for proposed solutions, including value quantification, analysis of return on investment and net present value, success metrics, and impl

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

As a Staff Product Manager on Datadog's Observability Data Platform (ODP) , you will lead product management for a portfolio of foundational platform bets — work that changes the cost structure and capability of the platform itself, not the cost of any single feature. Among ODP’s portfolio of engineering work are efforts to bring the platform's unit cost down meaningfully each quarter, plus a slate of architectural bets aimed at order-of-magnitude cost reduction over the longer horizon. The work you'll lead reshapes how Datadog ingests, routes, and exposes telemetry value to customers — and is foundational to how every product team in Datadog's ecosystem will think about telemetry economics going forward. This role reports to the Group Product Manager of ODP. What You'll Do: Set product direction across foundational platform bets by defining problems and desired outcomes, partnering with engineering to determine slices of work that drive value in phases for users and the business. Collaborate on the long-term cost-and-value architecture of the platform — how value-aware telemetry, innovative data engines, and customer-facing cost stories fit together over multiple quarters. Develop and defend sizing and impact estimates for large, diffuse programs — credibly produce the analysis that engineering leadership and pricing partners need to make resourcing and prioritization calls. Anticipate and communicate market trends in telemetry economics and agentic observability and how they shape platform investment. Develop deep understanding of cost-to-serve by partnering with engineering on the unit economics of the data platform and bring that cost-profile understanding into collaborative discussions with product verticals about customer-facing trade-offs. Surface the customer-positive angles in cost work that engineering-led optimization tickets don't currently make visible. Deliver concise written and verbal communication to executive, engineering, and customer audien

We are seeking a highly skilled and experienced Staff Network Site Reliability Engineer (SRE) to join our Enterprise Network Operations and SRE team. In this role, you will be pivotal in implementing our vision for a reliable and efficient network infrastructure. The ideal candidate is passionate about network operations and committed to enhancing the user experience. You'll have the opportunity to solve complex network challenges using hands-on debugging and by focusing on network automation, observability, documentation, and operational excellence. This is a critical position focused on ensuring user satisfaction and brilliance in network operations. What you'll be doing: Owning the operational aspect of the network infrastructure, ensuring its high availability and reliability, actively working on network incidents and service requests. Partnering with architecture and deployment teams to guarantee that new implementations are supportable and align with production standards. Advocating for and implementing automation to reduce toil and improve operational efficiency. Minimizing manual operational tasks to achieve and maintain Service Level Objectives (SLOs). Monitoring network performance, identifying areas for improvement, and collaborating with relevant teams to implement refinements. Proactively identifying and mitigating network risks to promote continuous improvement. Collaborating with domain experts across functions to resolve production issues swiftly and effectively, ensuring customer happiness. Conducting blameless postmortems and following through on Root Cause Analyses (RCAs). Discovering opportunities for operational improvements and teaming up with colleagues to devise solutions that enhance excellence and sustainability in network operations. Developing knowledge base articles for automa

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? Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll have opportunities to build expertise in advanced performance techniques, including GPU/CUDA optimizations, kernel-level improvements, and model execution strategies for MoE and large-scale architectures. 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, e

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: Building AI agents that can assist with any kind of enterprise work is a challenging, open-ended problem. One key piece of solving it is replicating real work environments as realistically as possible - filling them with hard tasks to solve, creating plausible input data, and defining clear rewards for completing the work the right way. We build many of these reinforcement learning (RL) environments, then drop our agents into them to evaluate or train them. In this role, you are responsible for creating these RL environments, running AI agents inside them, and improving both the agents and the environments in the process. The results reach customers, whose feedback feeds back in - and the agent/environment improvement loop continues. Key Responsibilities: There are many open problems in this space. As a Member of Technical Staff, RL Environments, you will: Build new RL environments targeting different agentic capabilities and industry areas Train and evaluate agents in those environments Make all the pieces work together: tasks, data, tool implementations, and verifiers Work across modeling and product to identify

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here). Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ Join us as a Staff AI Product Manager to enhance Qonto's customer experience through innovative solutions. You'll drive the maturity and scalability of our ML/AI capabilities, addressing concrete business problems while fostering innovation. You will work closely with Daniele Garbarino, our VP Data, to support AI products developments that significantly impact our 600,000+ customers' financial management experience. ➡️ What you'll do Own the AI product roadmap end-to-end: Define what we build, why, and in what order — gathering insights from engineering, data science, and business teams to develop a prioritized strategy that addresses real customer needs. Drive key AI product initiatives: Lead the definition and design of AI solutions for products like Attach

Note: if you are an intern, new grad, or staff applicant, please do not apply using this link and visit our jobs page for those specific postings. Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the Organization Secure Frameworks: We provide security guarantees for common threats, helping teams secure their services by default. We build and maintain core application-layer security libraries and frameworks for development teams, including web security frameworks, cryptography libraries, and other threat mitigations across the Stripe technology stack. More recently, our scope has expanded to protective measures for AI agents. We are a hands-on engineering team that builds security protections and frameworks, rather than conducting security reviews. Core Infrastructure : We’re the home for Stripe's critical tier0 infrastructure systems (Compute, Networking, DocumentDB, Distributed Caching and High assurance engineering). We build the foundational platform for Stripe products and services to allow them to operate at scale. We drive reliability, availability, efficiency and scalability of these systems. Developer Infrastructure : We’re responsible for the productivity of all developers at Stripe. Ensure Stripe’s engineers have a reliable, fast, and easy-to-use inner dev loop to maximize productivity while building everything from low-latency microservices to large-scale data pipelines and machine learning models. Reliability Insights and Excellence : We build tools and frameworks

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. ABOUT THE ROLE The Snowflake Cortex team is on a mission to bring the transformative power of generative AI and machine learning to enterprise customers, seamlessly and securely within the Snowflake Data Cloud. We are seeking an entrepreneurial and customer-obsessed Product Manager to lead the product vision and execution for our AI Solutions and Services. In this role, you will own the end-to-end product lifecycle for some of our most exciting AI services. You will be responsible for understanding customer needs, defining the product roadmap, and working with a world-class engineering team to deliver innovative solutions that make it easy for any user to leverage AI. You will sit at the critical intersection of customers, our forward-deployed engineering team, core engineering, and GTM strategy, driving the future of AI within the Data Cloud. If you are obsessed with building products that are both powerful and simple, and thrive on turning ambiguity into impact, this is the role for you. AS A STAFF APPLIED AI PRODUCT MANAGER AT SNOWFLAKE, YOU WILL: Own the Product Vision & Roadmap: Define and articulate a clear, compelling strategy for large-scale AI solutions. You will architect and own the end-to-end product lifecycle, from deep discovery and detailed requirements t