Ai Infrastructure Systems Engineer Jobs

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 researchers generate and depend on enormous amounts of data — training runs, evaluations, RL transcripts, annotations etc... The Research Data Platform team builds the systems that make that data easy to produce, find, query, and trust. We work in two modes: we build platform components that other systems plug into (for example, a metrics library that training frameworks integrate to record and retrieve run data), and we own core datasets end to end (for example, the data pipeline behind RL transcripts). As the team's tech lead, your job starts with our users. You'll work directly with researchers — and with the engineers who support them — to understand how they actually work, where managing data slows them down, and where a well-built platform component or a well-curated dataset would change what's possible. You'll turn what you learn into technical direction for the team, in partnership with the team's manager, who owns priorities and people. A central ambition you'll drive: a small set of canonical, well-documented datasets — starting with the core data model for RL — that researchers trust and standardize on, rather than every team managing its own copies. You'll spend your first few months close to the code and close to users: shipping improvements in our core systems, embedding with research teams, and building your own map of their workflows. As the team grows, this role has a natural path into formal people leadership for someone who wants it. Responsibilities Work directly with researchers and the engineers supporting them to understand their workflows, identify the highest-leverage opportuni

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We're seeking an exceptional Research Engineer to join our Life Sciences team at Anthropic. Our team is organized around the north star goal of accelerating progress in the life sciences, from early discovery through translation, by an order of magnitude. Our team likes to think across the whole model stack. In this role, you'll combine your deep expertise in machine learning engineering to develop novel evaluation frameworks and training strategies that push the frontier of what AI can achieve in biology. You'll work at the intersection of cutting-edge AI and the biological sciences, developing rigorous methods to measure and improve model performance on complex scientific tasks. You'll collaborate closely with world-class researchers and engineers to build AI systems that can engage in all phases of research and development, while maintaining our commitment to safety and beneficial impact. Previous experience in life sciences is welcome, but not required for this role. Minimum Qualifications Demonstrated experience training and evaluating large language models Proficiency in Python and familiarity with modern ML development practices Experience building and managing data pipelines for large-scale datasets Comfortable navigating ambiguity and developing solutions in rapidly evolving research environments Strong written and verbal communication skills, with the ability to work independently while collaborating effectively across cross-functional teams Preferred Qualifications 8+ years of machine learning experience Prior work experience in AI and biology, including graduate studies (molecular biology, biochemistry, comp

As a member of the AMER Solutions Org, you will act as a trusted advisor for prospects and clients, driving customer acquisition and accelerating revenue growth through a mastery of strategic sales and Asana platform expertise . In this role, you will be at the ground floor of an emerging go-to-market motion, partnering with a dedicated Account Executive to build repeatable technical plays for Asana Service Management across IT and service teams. You will bridge the gap between the voice of the business and the voice of the customer, gathering first-party insights to help shape how our product, demos, and technical positioning evolve . This role can either be fully remote or based in our New York City, San Francisco, or Chicago offices with an office-centric hybrid schedule . If based in-office: The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do and the teams with which you partner . If you're interviewing for this role, your recruiter will share more about the in-office requirements . What you’ll achieve Partner with the incubation Account Executive to lead technical validation for IT and service team opportunities within various customer segments and industries, managing everything from discovery to tailored product demonstrations and close. Translate complex customer pain points and service delivery workflows (such as request intake, triage, and fulfillment) into practical solution designs and compelling business value narratives for IT leaders. Advise customers on solution architecture, integrations, administration considerations, and deployment approaches to ensure a confident and seamless fit within their existing technology landscape. Collaborate cross-functionally with core Account Executives, Customer Success Managers, and core Solutions Engineers to uncover and support expansion opportunities within existing accounts. B

Command by Asana is a new product purpose-built for software development teams that helps engineers stay in flow Command automatically catalogs the decisions, context, and next steps agents need to stay efficient and keep moving. Engineers spend less time unblocking agents and more time on what’s next. Assists EMs with releases that de-risk themselves Command monitors scope, dependencies, pacing, and risks in real time, surfacing blockers and adjusting plans before they cascade into delays. Enables leaders to always know the status, without the meetings required Command gives leaders a custom, queryable view of the strategic work that's important to them, so they know what is truly at risk and why without waiting for a status update. We are building the first Solutions Engineering overlay team to support Command's go-to-market motion, partnering closely with customers to demonstrate how modern software teams can plan and execute with clarity, not theater. The Opportunity We're seeking a driven, entrepreneurial Solutions Engineer to join a newly formed team bringing Command to product development and Engineering teams. This is a unique opportunity to be on the ground floor of an emerging go-to-market motion, partnering with a dedicated Account Executive and cross-functional teammates to build repeatable technical plays that will scale across Asana's field organization. You will be an extended part of the Product Lead/General Manager's team, helping bring customer feedback to the product team and shape how the product, demos, and technical positioning evolve. You'll work with Engineering leaders, product development teams, and cross-functional stakeholders who are looking to modernize how they coordinate work, deflect repetitive requests, and deliver better employee experiences. This role requires strong technical curiosity and customer empathy—you'll lead discovery, technical validation, and solution design while partnering seamlessly with Asana's existin

Our sales team is focused on finding efficient paths to successful, profitable, long-term customers by building a user-driven marketing and sales engine . We act as a key voice of the customer to the product team, helping identify and overcome technical, educational, and competitive obstacles to our continued growth . In this role, you will join a newly formed team bringing Asana Service Management to IT and service teams, partnering with a dedicated Account Executive to build repeatable technical plays that scale across Asana's field organization. You will serve as an extended part of the product General Manager's team, translating customer pain points into practical solution designs while directly shaping how our product, demos, and technical positioning evolve. This role is based in our London office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do and the teams with which you partner . If you're interviewing for this role, your recruiter will share more about the in-office requirements . What you’ll achieve Partner with the incubation Account Executive to lead technical validation for IT and service team opportunities within various customer segments and industries, from discovery through proof, demo, and close Develop a deep understanding of IT and service management workflows—including request intake, approvals, triage, fulfillment, cross-functional coordination, and knowledge sharing—and map those workflows to Asana Service Management Translate customer pain points into practical solution designs and compelling business value narratives for IT leaders, service owners, and cross-functional stakeholders Conduct technical discovery sessions, whiteboard conversations, and tailored product demonstrations that position Asana within the customer's existing technology landscape Help custo

We're seeking a driven, entrepreneurial Solutions Engineer to join a newly formed team bringing Command by Asana to product development and engineering teams. This is a unique opportunity to be at the ground floor of an emerging go-to-market motion, partnering with a dedicated Account Executive and cross-functional teammates to build repeatable technical plays that will scale across Asana's field organization. You will be an extended part of the product General Manager's team, helping bring customer feedback to the product team and shape how the product, demos, and technical positioning evolve. You'll work with Engineering leaders, product development teams, and cross-functional stakeholders who are looking to modernize how they coordinate work, deflect repetitive requests, and deliver better employee experiences. This role requires strong technical curiosity and customer empathy—you'll lead discovery, technical validation, and solution design while partnering seamlessly with Asana's existing Account Executives, Customer Success Managers, and core Solutions Engineers to support both net-new and expansion opportunities. This role is ideal for someone who understands the Engineering buyer, thrives in ambiguity, loves building from the ground up, and is energized by the chance to help define a new market motion at Asana. This role can either be fully remote depending on where you live in the UK, or based in our London office with an office-centric hybrid schedule. If based in-office: The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Partner with the incubation Account Executive to lead technical validation for Engineering and product development opportunities within mid

Perplexity is seeking experienced ML engineers to design, build, and optimize the recommendation systems that power core experiences on Perplexity. Perplexity builds AI for those who expect more. Our products are designed to help people find answers, make their most consequential decisions, and complete increasingly ambitious work. Across these use cases, the Perplexity experience must feel deeply personal. Great recommendations and user understanding are central to delighting and delivering for each user. To do this, we are reimagining recommendation systems for the LLM era. Our goal is to combine the intelligence of frontier LLMs, the personalization context that comes from real product usage, and the continual learning capabilities of modern recommendation systems. We build systems that draw on past context and connected data sources to deeply understand each user's needs and recommend the actions that help them get the most out of Perplexity. Why Perplexity is Different Craftsmanship . We build high quality, tasteful products targeting both AI native and AI curious users. Ownership . You identify the problem, design the solution and ship it. Entrepreneurship . We think like founders, act with urgency, and hustle to deliver for each other and our users. Scholarship . Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. Partnership . We amplify each others’ strengths, break down silos, and give selflessly to help our colleagues deliver excellence. What you'll do Own the personalization and ranking behind key product surfaces to make Perplexity more useful and drive impact on core user and business metrics. Build user modeling that captures intent, preference, and propensity, and powers more relevant, more personalized experiences. Design the decision layer that balances competing objectives to produce the best overall experience for the user. Build the data and evaluation foundations that let these syst

In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, and the Growth team owns the product loops that help them discover, adopt, and build lasting habits around our most important AI experiences. As a growth engineer at Perplexity, you'll work across the full funnel — activation, onboarding, SEO, lifecycle, conversion, retention, and paid upgrade moments — while also building the applied AI systems that make those experiences smarter. Engineers are responsible for end-to-end projects from training and productionizing classifiers to identify high-intent users, personalizing value discovery, shipping contextual onboarding experiments, or wiring new AI capabilities into measurable adoption and revenue outcomes. Growth at Perplexity goes beyond incremental funnel optimization. The team sits close to the core product - we translate behavioral signals, model outputs, and fast experimentation into durable product surfaces used across consumer and enterprise workflows. You'll move fast, run many experiments in parallel, and own the outcome end-to-end. Tech Stack: TypeScript | Next.js | React | Python | PostgreSQL | Eppo | AWS Why Perplexity is different Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. Ownership. You identify the problem, design the solution and ship it. Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. What you'll do Design, build, and own growth surfaces across the full funnel — activation, onboarding, SEO, lifecycle, conversion, retention, and paid upgrade moments — for Computer and every P

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. We're seeking an exceptional Research Scientist to join our Life Sciences team at Anthropic. Our team is building a world-class research group focused on making Claude a superhuman life sciences research assistant. This role sits at the intersection of machine learning, software engineering, and biology — you'll directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development. As a core member of our Life Sciences team, you'll work in a high-impact team that translates deep biological domain knowledge into model training objectives, benchmarks, and agentic workflows. You'll help establish Anthropic as a leader in AI-accelerated biology while shaping how frontier models reason about and execute computational biology tasks. This role offers a unique opportunity to shape how frontier AI models learn to do biology. You'll work alongside some of the world's best AI researchers while tackling problems that matter for human health and scientific understanding. If you're excited about turning your computational biology expertise into model capabilities, we want to hear from you. Key Responsibilities Build and ship agentic tools and integrations that let Claude execute real life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review Design and build evaluation benchmarks that measure model capabilities on biology tasks — figure interpretation, bioinformatics, protocol reasoning, literature synthesis Work closely with product and design teams to scope, prototype, and ship features for life sciences users Partner with external biotech,

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 Computer Use team teaches Claude to see and operate computer interfaces, and builds the agent harness and end-user products that turn that capability into real tools. The team sits inside Anthropic's research organization and closes the loop between product and model. As a Product Engineer on this team, you'll own end-to-end delivery of our computer-use and browser-control product surfaces. You'll build across the full stack, from the user interface to the agent runtime to the backend services behind it. You'll work directly alongside researchers, with no layers between you and the model or the user. This is a dynamic role in which priorities evolve frequently. Success depends on a high tolerance for ambiguity, the adaptability to shift focus as needs change, and the agility and discernment to continuously prioritize the highest impact work. Key responsibilities Own end-to-end delivery of computer-use and browser-control product surfaces: scope, build, ship, measure, and iterate Diagnose and resolve reliability and robustness issues in the computer-use agent harness that block real-world usage Partner with computer-use researchers Partner with the Claude Cowork team on shared surfaces, integrations, and knowledge-worker workflows Instrument products and use usage data to drive prioritization and measure progress Translate fuzzy user pain points into concrete, shippable features for knowledge workers Minimum qualifications Experience building and shipping a product from zero to one with end-to-end ownership, as a founding or early engineer at a startup or with equivalent ownership inside a larger company

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building next-generation CPU and AI silicon. You’ll work at the forefront of hardware innovation, diagnosing complex issues across chips, systems, firmware, and software while collaborating with some of the brightest engineers in the industry. This role offers the opportunity to solve challenging technical problems, build impactful debug solutions, and directly influence the reliability and performance of cutting-edge AI compute platforms. This role is hybrid, based out of Toronto, Canada. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced in hardware debug and post-silicon bring-up for CPU, SoC, or ASIC systems. Strong understanding of processor architecture and microarchitecture (RISC-V, x86, or ARM) with familiarity in debug and trace methodologies (e.g., iJTAG). Hands-on engineer who excels at diagnosing complex hardware, firmware, and software issues through root-cause analysis. Comfortable working in the lab with a passion for building debug tools, automation, and scalable methodologies. Collaborative team player with experience partnering across ASIC, firmware, software, and validation teams. What We Need

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 inference fleet serves Claude to millions of users across our own products and the world's largest cloud platforms. The stack that makes this possible is deep and tightly coupled: accelerator kernels, model servers, distributed routing, autoscaling, capacity management. Every layer affects the others, often in ways that are hard to see in isolation. The Inference System Dynamics team is responsible for understanding that whole system and holding it to a high bar across four dimensions: throughput, latency, reliability, and correctness . We measure how the fleet performs against its theoretical performance frontier, run cross-layer investigations to explain the gaps, and own the correctness checks that make sure Claude's outputs are right, not just fast, across hardware platforms and serving configurations. We don't own the individual components. We instrument and model them, find the highest-leverage opportunities across them, and partner with the owning teams to land the wins. You'll work across all four areas. One week that might mean tracing a tail-latency regression from request timing down through routing and batching into a kernel overhead; the next it might mean tightening a correctness eval so it catches an output regression introduced by a quantization change. We're looking for performance engineers who treat correctness as part of performance. Key Responsibilities Run cross-layer performance investigations across throughput, latency, and reliability, sizing the gap between actual fleet performance and theoretical rooflines, identifying root causes, and quantifying the value of closing them Own and

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 production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. Decisions in production training depend on knowing how the model is really behaving. Our team's mission is to have the best observability into production post-training runs at Anthropic: to be the clearest, most trusted view of model quality during training. We shape what gets measured, keep the signal trustworthy and timely, and get to the bottom of surprising results to inform post-training and release decisions. In this role you will lead the science of how we evaluate production training runs. You'll work out which measurements tell us something real about the model, notice when they stop doing so, and find what we should be measuring but aren't. You'll partner with research teams across every RL domain, bringing their priorities into what we measure and setting the standard for what makes an eval trustworthy across post-training. You'll also be hands-on with the eval fleet day to day, because the best questions about measurement come from watching real results come in during a live run. Responsibilities Steer the eval strategy for production Claude models: study and optimize the eval mix so it gives the most accurate and complete assessment of model quality Run and monitor the eval fleet live to understand how each Claude model is developing as it trains Advise teams across post-training on eval methodology, and help eval authors bring new evals up to the bar for production Investigate regressions in production runs and inform training interventions when appropriate Build the