Ai Runtime Engineer Jobs

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Ray aims to provide a universal API for building distributed applications. To achieve this goal requires a distributed system with high levels of performance and reliability. We're looking for engineers with systems software experience that are interested in contributing to the Ray backend. About the Ray Core Team The Ray Core team develops and maintains the Ray C++ backend (e.g., distributed scheduler, language runtime integration, I/O and memory subsystems). We are responsible for the reliability, scalability, and performance of Ray as well as ensuring that Ray provides the right feature set to support higher level libraries and use cases. The team works on a balance of new features / distributed libraries, test infra improvements, debugging, and longer-term architectural improvements to Ray. A snapshot of projects you can work on: Optimizing performance of large-scale workloads on Ray Stability and stress testing infrastructure Improving fault tolerance (HA) As part of this role, you will: Leading cross-team projects while mentoring junior team members Develop high quality open source software to simplify distributed programming (Ray) Identify, implement, and evaluate architectural improvements

About the Team The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities. We enable OpenAI workloads to be qualified and optimized across new accelerator platforms without requiring a one-off port and tuning effort for every hardware target. Our work spans distributed systems, model execution, compilers and runtimes, performance engineering, secure partner integrations, evaluation systems, and developer tooling. We build the infrastructure that makes optimization workflows automated, reproducible, and trustworthy. About the Role We are seeking a software engineer to help build the platform that qualifies and optimizes inference workloads across heterogeneous compute environments. You will develop both OpenAI-hosted services and secure partner-side software for running long-lived optimization workflows. These workflows generate candidate kernels, runtime configurations, and serving-stack changes; compile and execute them on target hardware; verify their correctness; measure their performance; and use the results to guide further optimization. You will work across model architecture, distributed execution, compilers, runtimes, networking, and accelerator systems. A central part of the role is turning research prototypes and one-off hardware bring-up efforts into reliable, reusable infrastructure with clear contracts, reproducible results, strong observability, and well-defined security boundaries. Key Responsibilities Design, build, and operate APIs and control-plane services for long-running workload qualification and optimization campaigns, including scheduling, retries, checkpointing, resource budgets, and observability. Build secure partner-side execution and evaluation software that can compile, run, verify, profile, and benchmark candidate artifacts on accelerator hardware. Integrate model workloads, hardware profiles, compiler toolchains, runtimes, serving engines, and distributed-exe

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About this role Are you ready to redefine the future of JavaScript development? Are you a seasoned JavaScript expert who gets a thrill from tackling complex challenges across the entire JavaScript ecosystem? Do you believe that AI can be a powerful partner in crafting elegant, high-impact code? If you're ready to leave the mundane behind and join a team that's shaping the tools used by millions of developers globally, we've got an opportunity for you at Sentry. This isn't your typical Senior Software Engineer position. As a key member of our growing JavaScript SDK team, you'll be at the forefront of innovation, working on everything from our cutting-edge SDKs for Node.js, Bun, Deno, Cloudflare Workers, and other modern server runtimes. You won't just be maintaining code; you'll be pushing the boundaries of what's possible in developer tooling across the rapidly evolving server-side JavaScript landscape. In this role you will Join our JavaScript SDK team and get ready to build the future. You'll be at the forefront, working on: A Universe of JavaScript Challenges: Dive deep into our extensive suite of JavaScript SDKs, with a sharp focus on server-side and edge runtimes — from the battle-tested Node.js ecosystem to cutting-edge alternatives like Bun and Deno, and distributed edge environments like Cloudflare Workers. Your work will directly empower millions of developers to build better, more reliable software, no matter which runtime powers their stack End-to-End Ownership: We believe in giving our engineers the autonomy to see their vision through. You'll have the freedom to plan, implement, and ship your code, from writing

We are hiring an experienced Security Software Engineer (Staff or Senior) for our Infrastructure Security team to design and build scalable security controls and services within MongoDB Atlas multi-cloud infrastructure. The team sits within the Site Reliability Engineering organization and works with other engineering teams to ensure that our infrastructure adheres to the highest security standards. This role can be based out of our Dublin office, or work fully remotely in Ireland. Responsibilities: Design and build core security primitives and services that protect MongoDB Atlas compute, networking, and identity across AWS, Azure, and GCP Build secure-by-default infrastructure using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups), Kubernetes, and eBPF to enforce runtime policies and gain deep visibility into systems behaviour Develop APIs, automation, and tooling that manage security posture at scale (CSPM, vulnerability management, workload identity) and provide monitoring, logging, and alerting pipelines that integrate with our tooling (Grafana, Splunk, Victoria Metrics.) Integrate security into our CI/CD and infrastructure-as-code workflows (Terraform) so that security controls are versioned, reviewed, and deployed just like any other code Lead complex projects end‑to‑end, from problem discovery and design docs to implementation, rollout, and long‑term ownership Collaborate with SRE, platform and product engineering teams to define secure architectures for new infrastructure and services Qualifications: You might be a great fit if you match some of the following: 5+ years of experience in Software Engineering, Site Reliability Engineering, or similar roles, preferably with relevant security work Proficiency with at least one programming language (Java, Golang, Rust, Python, or C/C++) and experience with infrastructure-as-code tools (Terraform) to automate security configurations and processes A deep understanding of Linux and networking concepts,

We are hiring an experienced Security Software Engineer (Staff or Senior) for our Infrastructure Security team to design and build scalable security controls and services within MongoDB Atlas multi-cloud infrastructure. The team sits within the Site Reliability Engineering organization and works with other engineering teams to ensure that our infrastructure adheres to the highest security standards. This role can be based out of our New York City, Austin, Seattle or San Francisco offices, or work fully remotely on standard East Coast business hours. Responsibilities: Design and build core security primitives and services that protect MongoDB Atlas compute, networking, and identity across AWS, Azure, and GCP Build secure-by-default infrastructure using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups), Kubernetes, and eBPF to enforce runtime policies and gain deep visibility into systems behaviour Develop APIs, automation, and tooling that manage security posture at scale (CSPM, vulnerability management, workload identity) and provide monitoring, logging, and alerting pipelines that integrate with our tooling (Grafana, Splunk, Victoria Metrics.) Integrate security into our CI/CD and infrastructure-as-code workflows (Terraform) so that security controls are versioned, reviewed, and deployed just like any other code Lead complex projects end‑to‑end, from problem discovery and design docs to implementation, rollout, and long‑term ownership Collaborate with SRE, platform and product engineering teams to define secure architectures for new infrastructure and services Qualifications: You might be a great fit if you match some of the following: 5+ years of experience in Software Engineering, Site Reliability Engineering, or similar roles, preferably with relevant security work Proficiency with at least one programming language (Java, Golang, Rust, Python, or C/C++) and experience with infrastructure-as-code tools (Terraform) to automate security configurations

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations: Austin, TX About the Role Cloudflare’s Emerging Technologies & Incubation team builds and launches bold new products on Cloudflare’s edge network. This role is on the Durable Objects team, which powers stateful serverless applications for Cloudflare customers. You’ll help evolve the runtime and the low-level routing and storage systems that support real-time chat, multiplayer games, AI agents, and other stateful workloads at sca

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

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Ray aims to provide a universal API for building distributed applications. To achieve this goal requires a distributed system with high levels of performance and reliability. We're looking for engineers with systems software experience that are interested in contributing to the Ray backend. About the Ray Core Team The Ray Core team develops and maintains the Ray C++ backend (e.g., distributed scheduler, language runtime integration, I/O and memory subsystems). We are responsible for the reliability, scalability, and performance of Ray as well as ensuring that Ray provides the right feature set to support higher level libraries and use cases. The team works on a balance of new features / distributed libraries, test infra improvements, debugging, and longer-term architectural improvements to Ray. A snapshot of projects you can work on: - Optimizing performance of large-scale workloads on Ray - Stability and stress testing infrastructure - Improving fault tolerance (HA) As part of this role, you will: Develop high quality open source software to simplify distributed programming (Ray) Identify, implement, and evaluate architectural improvements to Ray core Improve the testing process for Ray to make re

As a member of the HW Infrastructure Storage Strategy team, you will be the bridge between storage infrastructure and the chip design (e.g. NVIDIA GPUs and CPUs) workloads that depend on it. You will focus on going hands-on to understand how storage behavior impacts EDA (Electronic Design Automation) and HPC workload performance in general — and what to do about it. You’ll evaluate next-generation storage technologies, design POCs grounded in real workload profiles, uncover gaps in observability, and drive strategic decisions like data placement during datacenter transitions. This is a rare role where you’ll work at the intersection of storage systems and chip design workflows at a scale few companies reach — petabytes of active data, millions of files per job, and thousands of concurrent users. You’ll develop NVIDIA’s storage strategy and have a direct, measurable impact on engineering velocity. What you'll be doing: Lead storage technology evaluations — design and execute POCs for platforms such as NetApp, VAST, and others, using real EDA workload profiles to benchmark performance, metadata behavior, and compatibility Analyze how storage configurations and architecture choices impact EDA workload runtime in production, and recommend tuning or architectural changes to reduce job execution time Identify gaps in storage telemetry and observability — define what metrics are needed and how to correlate storage behavior with jobs running on the environment Support datacenter lifecycle programs — expansions, technology refreshes, and site exits — by mapping workload placement, identifying required data, and minimizing data replication scope Define storage policies and best practices — data lifecycle, tiering strategies, snapshot/clone workflows (e.g., FlexClone for EDA workspace branching), and capacity planning recommendations Collaborate with IT, EDA tool teams, EDA operations, and

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Our transport network serves the needs of millions of people every day who want to get from one place to another using Lyft cars, bikes and scooters, or on foot in the most efficient way. To serve these needs, we need to suggest the fastest, most affordable and safest routes. We are hiring a Machine Learning Engineer to join our Routing team. Our team builds and maintains Lyft's system responsible for providing routes for every ride request on our platform. We process millions of route requests per day and low latency, high reliability and high accuracy are paramount for our success. If you are a critical thinker with experience in machine learning workflows and writing reliable code, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. Our technology stack runs on AWS, Kubernetes, Go, Python/C++, Apache Airflow, Flink, and Kafka. We use AI to improve development productivity, optimize customer support workflows, and enhance operational efficiency — all without compromising code quality or security. In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers. Responsibilities: Perform data analysis and build proof-of-concept to explore and compare ML and non-ML solutions Be able to make effective tradeoffs between model accuracy, its productization complexity and runtime performance Develop statistical, machine learning, or optimization models Write production quality code that can scale well to serve millions of requests per day Participate in code reviews, design reviews, production on-call support and incident triaging process

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Streaming Platform team at Sentry is building the next generation of infrastructure that powers our ingestion pipelines and real-time data processing systems. Our platform ingests, processes, and distributes hundreds of thousands of events per second with low latency and high reliability. We are creating a system that makes it easy for Sentry engineers to deploy and run Streaming Applications at scale by simplifying the complexity of Kafka, scaling consumers automatically, and managing state so product teams can focus on building great experiences for developers. As part of this team, you will work on challenges at the intersection of distributed systems, real-time data processing, and developer experience. You will help us create a self-service streaming platform that improves stability, accelerates time to production, and reduces operational overhead. This role is based in Toronto, with three days per week in the office to work closely with engineering teams. In this role you will Design, build, and operate components of our Streaming Platform, including Kafka, the streaming runtime, high-level APIs, and developer-facing abstractions. Implement resilient, high-throughput stream processing systems that handle unbounded datasets with strong correctness guarantees (delivery, checkpointing, watermarking, and more). Build scalable automation and control plane for Kafka fleet management and improve efficiency. Partner with product engineers to ensure our abstractions enable fast, reliable, and consistent ingestion pipelines. Improve observability, monitoring, and failover for mission-critical real-time systems

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Streaming Platform team at Sentry is building the next generation of infrastructure that powers our ingestion pipelines and real-time data processing systems. Our platform ingests, processes, and distributes hundreds of thousands of events per second with low latency and high reliability. We are creating a system that makes it easy for Sentry engineers to deploy and run Streaming Applications at scale by simplifying the complexity of Kafka, scaling consumers automatically, and managing state so product teams can focus on building great experiences for developers. As part of this team, you will work on challenges at the intersection of distributed systems, real-time data processing, and developer experience. You will help us create a self-service streaming platform that improves stability, accelerates time to production, and reduces operational overhead. This role is based in San Francisco, with three days per week in the office to work closely with engineering teams. In this role you will Design, build, and operate components of our Streaming Platform, including Kafka, the streaming runtime, high-level APIs, and developer-facing abstractions. Implement resilient, high-throughput stream processing systems that handle unbounded datasets with strong correctness guarantees (delivery, checkpointing, watermarking, and more). Build scalable automation and control plane for Kafka fleet management and improve efficiency. Partner with product engineers to ensure our abstractions enable fast, reliable, and consistent ingestion pipelines. Improve observability, monitoring, and failover for mission-critical real-time s

Location Qualifications: This role is available for hybrid work (2 days in office) from our office in Bucharest. About the position As a Backend Engineer, you'll be pivotal in crafting innovative solutions that transform the creation, organization, and distribution of sales content. Catering to Sales Enablement specialists and Marketing Content Owners, you'll harness cutting-edge technologies to continuously elevate our platform, maximizing its impact on our users. Your role will involve not just expanding and refining our codebase, but also driving innovation for new features. You’ll take full ownership, writing functional, automated, and scalable code that operates seamlessly within our cloud infrastructure and is efficiently monitored. Key Responsibilities Develop high-throughput, maintainable backend services and API integrations using Node.js, TypeScript , or Go. Design cloud-native microservices and serverless workflows optimized for resilience, speed, and cost efficiency. Take features from design and technical RFCs through development, automated testing, CI/CD, and production deployment. Lead impactful code reviews, mentor teammates, and refine operational standards like observability, telemetry, and alerting. Identify bottlenecks across storage, databases, and network layers to keep platform latency minimal as we scale. Required Skills 3+ years of hands-on experience building production-grade backend systems. Strong proficiency in at least one modern language/runtime: TypeScript, Node.js, or Go. Experience architecting and deploying services on AWS (e.g., Lambda, ECS/EKS, DynamoDB, SQS/SNS, RDS). Practical understanding of distributed systems, API design (REST/GraphQL/gRPC), caching strategies, and telemetry (Datadog, OpenTelemetry, etc.). Strong commitment to automated testing (unit, integration, e2e) and continuous deployment practices. Excellent asynchronous communication skills and a preference for building iteratively in agile environments. Comp

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About Vercel: Vercel gives developers the tools and cloud infrastructure to build, scale, and secure a faster, more personalized web. As the team behind v0, Next.js, and AI SDK, Vercel helps customers like Ramp, Supreme, PayPal, Chick-fil-A, and Under Armour build for the AI-native web. Our mission is to enable the world to ship the best products. That starts with creating a place where everyone can do their best work. Whether you're building on our platform, supporting our customers, or shaping our story: You can just ship things. About the Role: We're looking for a Software Engineer to join the Next.js team . In this role, you'll work on the core of the framework, collaborating directly with the open-source community, shaping the future of the web, and delivering impactful features to a global audience of developers. Our team is responsible for advancing Next.js and its ecosystem, enabling developers to build faster, more scalable, and more performant applications. If you’re passionate about web standards, open source, and developer experience, you’ll thrive here. You’ll work on challenges such as server rendering, routing, bundling, performance optimizations, and integrating emerging web standards – all while ensuring the framework remains intuitive and stable. What You Will Do: Design and implement core features in Next.js, from RFC to release Collaborate with internal teams (like Vercel’s platform and runtime teams) to build seamless integrations between framework and infrastructure Engage with the open-source community through issues, PRs, R