Staff Power And Performance Validation Engineer in United States

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

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 Runway Runway is a collaborative business planning platform designed to make business intuitively understandable for everyone. Our Mission : To make business accessible and understandable to everyone. We believe that teams that understand the “why” behind their work are more productive and make better decisions. True alignment and collaboration come from having a shared source of truth that everyone understands. Our Approach : Runway replaces traditional spreadsheets with a modern planning platform that brings clarity and context to business operations for all teams — not just finance. Just as Figma made design accessible across the organization, Runway does the same for business planning. Why It Matters: Understanding requires more than just access to numbers; real collaboration happens when teams see how their work fits into the bigger picture. By providing this context, Runway helps teams save time and move faster. Our Customers : World-class companies like AngelList, Superhuman, Stability.AI, ConvertKit, Lambda Labs, Lob, and SandboxVR rely on Runway to run their businesses more efficiently. Our Investors : We are supported by a select group of investors that we admire, including Garry Tan (YC & Initialized), a16z, Elad Gil, Naval Ravikant, Dylan Field (founder of Figma), Eric Ries, Claire Hughes Johnson (COO of Stripe), Henry Ward (founder of Carta), Akshay Kothari (COO of Notion), Eugene Wei, Lenny Rachitsky, Nikita Bier, Scott Belsky, Soleio Cuervo, Balaji Srinivasan, and many others. Working at Runway We're remote-first, so you can work from anywhere in North America. We strive to be clear in our communication and over-communicate by default. It’s early in our journey, so you'll have an opportunity to shape not just our product, but the company itself: how we work together, what makes us stand out, and who we hire. Below are the values we share as a team — if these resonate with you, you may enjoy working here. (And if you don't like them, please t

About Runway Runway is a collaborative business planning platform designed to make business intuitively understandable for everyone. Our Mission : To make business accessible and understandable to everyone. We believe that teams that understand the “why” behind their work are more productive and make better decisions. True alignment and collaboration come from having a shared source of truth that everyone understands. Our Approach : Runway replaces traditional spreadsheets with a modern planning platform that brings clarity and context to business operations for all teams — not just finance. Just as Figma made design accessible across the organization, Runway does the same for business planning. Why It Matters: Understanding requires more than just access to numbers; real collaboration happens when teams see how their work fits into the bigger picture. By providing this context, Runway helps teams save time and move faster. Our Customers : World-class companies like AngelList, Superhuman, Stability.AI, ConvertKit, Lambda Labs, Lob, and SandboxVR rely on Runway to run their businesses more efficiently. Our Investors : We are supported by a select group of investors that we admire, including Garry Tan (YC & Initialized), a16z, Elad Gil, Naval Ravikant, Dylan Field (founder of Figma), Eric Ries, Claire Hughes Johnson (COO of Stripe), Henry Ward (founder of Carta), Akshay Kothari (COO of Notion), Eugene Wei, Lenny Rachitsky, Nikita Bier, Scott Belsky, Soleio Cuervo, Balaji Srinivasan, and many others. Working at Runway We're early, so you'll have an opportunity to shape not just our product, but the company itself: who we work with, and how we work together. We strive to be clear in our communication and over-communicate by default. We're remote-first, so you can work from anywhere in North America. However, we also believe in the value of face-time to solve really hard problems, so we: Meet together as a company every quarter in our San Francisco office. Open up of

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! Member of Technical Staff, Search Why this role? We are looking for talented individuals to help us develop state-of-the-art models for information retrieval as part of our Search team. This group is working on a range of tasks including training our embedding and reranker models. You'll have the opportunity to revolutionise people's search experience by contributing to building an intelligent, efficient and precise search system and you would have a lot of opportunity to try new things out, innovate, and productionize your ideas. Your work will specifically focus on advancing semantic search techniques to improve accuracy and efficiency, involving working with a wide range of novel technologies and collaborating with other teams to integrate your work into our search infrastructure. We're looking for someone who is passionate about search and has a strong background in information retrieval. Candidates should have experience working with a wide range of technologies and have worked collaboratively with other teams in the past. As a Member of Technical Staff on this team, you will: Design, train and improve upon cutting-edge sea

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 Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

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 Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

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! The Chief of Staff is a strategic leadership role focused on optimizing sales operations, enabling revenue growth, and ensuring alignment between sales execution and company objectives. This exciting career opportunity offers a blend of operational oversight, strategic planning, and cross-functional collaboration. Key Responsibilities Sales Strategy & Execution: Partner with the CRO to define and implement sales strategies, forecasts, and performance metrics. Operational Excellence: Streamline sales processes, including pipeline management, CRM optimization, and sales enablement tools. Cross-Functional Coordination: Work closely with marketing, product, and customer success teams to ensure cohesive go-to-market execution. Performance Analytics: Monitor sales KPIs, conduct data-driven insights, and recommend adjustments to improve conversion rates and revenue attainment. Team Leadership: Contribute to sales operations, business development, and support functions, fostering a high-performance culture. Stakeholder Management: Serve as a liaison between sales leadership and executive teams, ensuring clear communication and strat

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? Are you energized by leading the design of high-performance, scalable and reliable machine learning systems? Do you want to set technical direction and help shape the next generation of AI platforms powering advanced NLP applications? We are looking for a Lead Member of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will provide technical leadership across multiple teams, driving the architecture and strategy for deploying optimized NLP models to production in low latency, high throughput, and high availability environments. You will serve as a key point of contact for customers, leading the design of customized deployments to meet their specific needs, and mentoring engineers to raise the technical bar across the team. You may be a good fit if you have: 8+ years of engineering experience running production infrastructure at a large scale, with a track record of technical leadership Demonstrated experience leading the architecture

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart's mission is to create a world where everyone has access to the food they love and more time to enjoy it together. Online Grocery is the heart of that mission — the products millions of customers rely on every day and the team that builds them. We

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. Position Overview: As a Staff/Principal Equipment Engineer within PROCT ADT, you will provide technical leadership to improve equipment performance, capability, and global manufacturing outcomes. You will lead complex, multi-site initiatives to resolve equipment challenges, enable technology node readiness, and drive yield and defectivity improvements. This role requires deep expertise, strong ownership, and the ability to influence across teams and suppliers to deliver measurable impact in cost, performance, and scalability. Responsibilities Lead global ownership of equipment performance across toolsets, driving improvements in stability, availability, matching, and efficiency. Direct complex, multi-fab root cause analysis for equipment-driven yield, defectivity, and reliability issues using data-driven and physics-based approaches. Provide technical leadership in tool hardware and chamber behavior to expand process capability and improve performance limits. Partner with Technology Development, integration, and process teams to enable node readiness, volume ramp, and disciplined change control. Influence equipment supplier strategy by leading technical engagements, driving design improvements, and aligning roadmaps to business needs. Drive global standardization through development, validation, and deployment of Best Known Methods (BKMs) across sites. Lead initiatives to improve cost of ownership, reduce variation,

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 and AI Agent Development Lead, you will lead the design, development, and deployment of next-generation AI agents that interact with users and complex environments. You will drive the architecture and implementation of scalable, reliable AI systems, working closely with research, product and engineering teams to build safe, interpretable, and performant AI technology. What You’ll Do Lead a cross-functional engineering team focused on AI agent development, from conceptual design to production deployment. Design and implement AI agent architectures leveraging state-of-the-art language models and associated technologies. Collaborate with research scientists on scalable experiments and productize research innovations. Drive the development of agent capabilities including dialogue management, decision making, and autonomy. Ensure AI safety and alignment principles are integrated throughout the agent lifecycle. Mentor and grow technical staff, fostering an environment of collaboration and innovation. Evaluate new tools, frameworks, and methodologies to enhance AI agent capabilities. Partner

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 Postman is seeking an experienced AI Systems Reliability Engineer to help define, build, and maintain the infrastructure and processes that ensure the reliability, scalability, and performance of Postman’s AI-powered API and agentic systems in production. This role focuses on monitoring, availability, incident response, and automation to support AI services and tools trusted by millions of developers globally. What You’ll Do Develop and manage reliability metrics (SLOs) for AI-driven API services and agentic AI platform features Implement comprehensive observability and monitoring systems for real-time performance and fault detection Design and drive automated failover, recovery, and incident response strategies for high-availability AI infrastructure Optimize resource utilization, particularly GPU/accelerator efficiency, ensuring cost-effective AI system operation Collaborate closely with engineering, platform, and product teams to align reliability efforts with broader organizational goals Lead efforts to build internal tooling and automation focused on AI system stability and operational excellence Drive continuo

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role Overview As Chief of Staff to the CEO, you will be the strategic nerve center of the entire company — a true force-multiplier to Surojit Chatterjee (ex CPO Coinbase, VP Products at Google). Reporting directly to the CEO and based in Mountain View, CA (full co-location required), you will own the translation of the CEO's vision across Sales, Product, and the full organizational agenda — serving as connective tissue between the CEO and every critical function: EPD, GTM, Finance, HR, Legal, and the Board. This is a senior operating role for someone who has already done it — led strategy at scale, driven GTM at a high-growth technology company, and earned their stripes as an Engagement Manager or Associate Principal at a top-tier consulting firm (McKinsey, BCG, Bain) before stepping into industry. You are not here to learn the ropes; you are here to pull them. Ema is backed by top-tier investors (Accel, Section 32, and Prosus) and is building the Universal AI Employee for enterprises worldwide. This is a high-visibility, high-impact role at one of the most consequential AI companies in the world. Key Responsibilities CEO Leverage & Executive Operations Serve as Surojit's strat