Staff Senior Product 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: Multi-Agent systems are becoming an increasingly important part of how AI is deployed, whether via fast small-model subagents inside a product, or large groups of agents solving very large problems . Training Claude to be maximally effective and safe within large groups is a challenging new area of reinforcement learning, and represents a new axis for scaling test time compute. We are looking for researchers who have experience training multi-agent systems at the largest scale and an appreciation for the incentives and mechanism design that come into play. Responsibilities: Help create and optimize environments and data for model training that maximize Claude’s performance or ease of use on agentic tasks Ideate, develop, and compare the performance of different agent harness configurations (eg memory, context management, communication architectures for agents) Design and implement rigorous quantitative benchmarks for large scale agentic tasks Work with our product org to find solutions to our most vexing challenges in applying agents to our products You may be a good fit if you: Have experience with large-scale RL on language models Have experience training multi-agent systems Enjoy going deeply into the roots of a problem and understanding its foundations, rather than its surface. Have good communication skills and an interest in working with other researchers on difficult tasks Have a passion for making powerful technology safe and societally beneficial Are excited for a mission-driven org with fast-paced, impactful work Representative projects: Design and build reinforcement learning environments to train groups of

Staff Software Engineer - Money Team P-940 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure). As a software engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market. By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem. The impact you

P-57 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping work on top priorities for the company. The Data team also functions as an in-house, production "customer" that dog foods Databricks and drives the future direction of the products. The impact you will have: “ Analysis at the speed of thought ”: Inform decision making by building robust data science tooling for business leaders, analysts, and other data scientists. “ Extend capabilities of Databricks ”: Work closely with Data Platform and Product Engineering teams to integrate data science tooling with existing Data team offerings and the core product “ Strategic bus

P-988 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Data Plane Storage : Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Delta Lake : A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture. Delta Pipelines : It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and pos

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. Our Tensix team is building custom AI compute cores, RISC-V CPUs, and chiplet-based architectures for datacenter, edge, and automotive AI. Design Verification Engineers on this team validate compute IP and subsystems and build scalable DV infrastructure to keep verification fast, automated, and production-grade. This role is hybrid, based out of Toronto, ON, Austin, TX or Belgrade, Serbia. 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 modern verification methodologies with strong SystemVerilog skills and exposure to structured testbench development. Comfortable working from block-level to system-level verification and reasoning about microarchitecture behavior from specs and waveforms. Proficient in Linux environments with Python, or Bash scripting for automate builds, parse logs, manage CI pipelines. Skilled in coverage-driven verification and confident debugging across RTL, testbench, and workload scenarios. Motivated by AI hardware and eager to learn verification strategies for new architectures and domains. What We Need Contribute to verification of Tensix IP and subsystems from early planning through tape-out, owning cov

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary: With data such as a billion+ historical job postings, tens of millions of active job seekers interacting with our system, and hundreds of billions of impression and click events, there are incredible opportunities to use your skills to build new data-driven features. Working at ZipRecruiter, you will be helping literally millions of people find their dream job. We’re working on problems like: given a training set of job postings, and known salaries, build a system that predicts salary for novel jobs.Of course, you know that while building models is fun, it's also just one step in the process; gathering training data, cleansing it, digging into it, extracting features from it, etc, is a huge part of the job Key Focuses: Design, develop, and maintain advanced machine learning models and algorithms to solve complex business problems Lead complex machine learning projects that solve business challenges and add value to the broader ZipRecruiter Business Design the overall architecture and infrastructure for machine learning systems, ensuring scalability, efficiency, and robustness Push the boundaries of what's possible in machine learning in your organization, finding new and innovative ways to use AI to drive business value Provide leadership and set tone for Machine Learning Engineers at ZipRecruiter leveraging industry best practices an

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary: With data such as a billion+ historical job postings, tens of millions of active job seekers interacting with our system, and hundreds of billions of impression and click events, there are incredible opportunities to use your skills to build new data-driven features. Working at ZipRecruiter, you will be helping literally millions of people find their dream job. We’re working on problems like: given a training set of job postings, and known salaries, build a system that predicts salary for novel jobs.Of course, you know that while building models is fun, it's also just one step in the process; gathering training data, cleansing it, digging into it, extracting features from it, etc, is a huge part of the job Key Focuses: Design, develop, and maintain advanced machine learning models and algorithms to solve complex business problems Lead complex machine learning projects that solve business challenges and add value to the broader ZipRecruiter Business Design the overall architecture and infrastructure for machine learning systems, ensuring scalability, efficiency, and robustness Push the boundaries of what's possible in machine learning in your organization, finding new and innovative ways to use AI to drive business value Provide leadership and set tone for Machine Learning Engineers at ZipRecruiter leveraging industry best practices an

P-940 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark™, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructu

P-186 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Da

P-186 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Da

P-188 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Experience working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 8+ years of experience working in a related system (preferred) Optional: PhD in databases or distributed systems Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are

P-188 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Experience working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 8+ years of experience working in a related system (preferred) Optional: PhD in databases or distributed systems Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are

Who we are At Fluxon, we believe that how you build matters as much as what you build. We help businesses navigate their most important technology decisions with confidence, and take responsibility for seeing them through. Founded by ex-Googlers and startup veterans, we’re proud to partner with teams behind some of the most ambitious products, including Google, OpenAI, Anthropic, Walmart and Stripe. Our work spans strategy, design, and engineering — often in complex, AI-driven environments — where clarity, speed and quality are the standard. We use AI intentionally, applying it only where it adds real value and expands what’s possible. Care shapes everything we do. Inside Fluxon, you’ll find a global, remote-first team of experienced builders, who are curious, kind and serious about their craft. We’re building a place where people can take ownership, solve problems that matter and do work they’re proud to stand behind. If you want to do your best work alongside people who care as much as you do, you’ll feel at home here. Note: This position is fully remote and open to candidates based anywhere in Portugal. About the role As a Staff Software Engineer at Fluxon, you'll drive the end-to-end delivery of products to market while learning, contributing, and growing in partnership with our leadership team You'll be responsible for: Guiding project delivery all the way to the user, leading projects, building and iterating in a dynamic environment Partnering directly with clients to understand their needs, and achieve business goals Defining product requirements, identifying appropriate system designs and planning development in partnership with our Product and Design teams Supporting development of a healthy and effective engineering culture You'll work with a diversity of technologies, including: Languages TypeScript/JavaScript, Java, .Net, Python, Golang, Rust, Ruby on Rails, Kotlin, Swift Frameworks Next.js, React, Angular, Spring, Expo, FastAPI, Django, Swif

P-150 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Our te

P-150 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark™, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Our