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Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role can be based out of our New York City office or remotely within the United States and Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Po

Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role will be based remotely in Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Position Expectations Understand and improve the current funct

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 London, UK About the Role Anytime we push code, it automatically affects the millions of Internet properties (powering websites, remote teams, APIs, mobile apps, etc.) running on our global network. Cloudflare's network is one of the largest in the world and spans over 330 cities in more than 125 countries. What's more, Cloudflare operates within 50 milliseconds of 95% of the Internet-connected population globally (for context,

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team Our AI research team sits at the heart of our mission to unlock new dimensions of biological understanding. You will leverage state-of-the-art AI to accelerate discovery and drive transformative insights in biology—developing novel AI models purpose-built for biological research, engineering robust systems that enable breakthrough science at unprecedented scale, and translating these advances into practical tools that empower researchers worldwide. Our approach is comprehensive and integrated, bringing together world-class AI model development, exceptional engineering talent, high-quality biological data, powerful computing infrastructure, and strategic partnerships. Success requires excellence across five interconnected pillars: training frontier AI models specifically for biology; building engineering systems that maximize research velocity and efficiency; executing a sophisticated data strategy that fuels AI development; operating a world-class AI compute platform; and creating impactful products that transform AI capabilities into accessible scientific tools. The Opportunity The Security Engineering and Infrastructure team brings modern security engineering practices to the Biohub network to make sure our systems are secure while we accelerate Biomedical research. We are uniquely positioned to design, build, and scale software systems to help scientists better address the myriad challenges they face. This team works on building shared tools and platforms to be used across

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The AI Cluster Production Engineering team is part of the AI Compute Platform organization at Biohub, a non-profit research lab committed to open science and open-source AI. We own the design, operation, and reliability of large-scale multi-GPU AI clusters that power frontier AI biology research: protein language models, genomic foundation models, and scientific reasoning systems built to be shared, not monetized. Our clusters run Slurm on Kubernetes infrastructure and support everything from day-to-day AI researcher workflows to multi-node hero training runs at thousands of GPUs. The team works at the intersection of AI tooling, distributed systems, HPC, and frontier AI, debugging deep AI infrastructure problems and building AI systems critical to the entire AI organization. The Opportunity CZ Biohub's mission is to cure or prevent all human disease. Achieving that requires training frontier-scale AI biology models, and that demands reliable, high-performance compute infrastructure. This is production engineering work at a frontier AI lab, with the twist that the mission is biology and the science is open. You'll keep GPU clusters running at high utilization, debug the toughest distributed systems failures, and build the operational foundations for scaling to multi-thousand GPU hero runs. The technical problems are genuinely hard (e.g., multi-node distributed training, InfiniBand fabrics, large-scale storage, Slurm at scale) inside an organization where the work is aimed at helping peop

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Container runtimes were designed for general-purpose software workloads. AI inference is not a general-purpose workload. Running large models at production scale exposes cracks in every layer of the container stack: runtimes unaware of GPU memory constraints, images that take minutes to pull when a model needs to scale to thousands of replicas, and isolation mechanisms that weren't designed for the multi-tenant serving environments that production AI requires. The tools the industry has relied on for a decade weren't built for this, and patching around those limitations at higher layers only goes so far. Baseten owns the entire pipeline, from the moment a developer pushes a model to the moment a request gets a response. That vertical ownership means we can fix these problems at the root. The Runtime Fabrics team is doing exactly that: purpose-building the container runtime and storage layers for AI inference workloads, led by some of the world's top containerd maintainers. As Engineering Manager of the Runtime Fabrics team, you will lead this work, setting technical direction, growing a world-class team of systems engineers, and ensuring the team's output shapes not just Baseten's infrastructure but the open-source container ecosystem at large. If you've contributed to containerd, runc, or related OCI projects and are ready to lead a team solving some of the hardest problems in infrastructure today, we'd love

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE We’re seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Core Engineering Responsibilities Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap Performance & Innovation Impl

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 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 (e.g. a machine learning pipeline of feature engineering, model training, and evaluation). Data is usually a core element connecting these different stages, and therefore plays a critical role in Ray’s usability, performance, and stability. We are looking for strong engineers to build, optimize, and scale Ray’s Datasets library and data processing capabilities in general. About the Ray Data team: The Ray Data team currently develops and maintains the Ray Datasets library, which is already powering critical production use cases (e.g. large scale data compaction at Amazon , and ML pipeline at Alibaba ). Ray Datasets is a Python library built on top of Apache Arrow and Ray Core (Ray’s C++ backend), and the Ray Data team interacts closely with Ray Core components including the scheduler and the memory & I/O subsystems. The Ray Data team also works closely with Ray’s ML libraries including Train, RLlib, and Serve. A snapshot of projects you will work on: - Performance of Ray Datasets at large scale (leveraging Arrow primitives, optimizing Ray object manager, etc.) - Integration with ML training and data sources - Stability an

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

Who We Are Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future. About the Role The Mapping team in Nuro takes a machine learning-first path to unblock geographic capability with lower costs. This team plays a crucial role in the advancement of autonomous driving systems by creating and improving different components in the full lifecycle of ML models for multiple teams in this organization. We are searching for an engineer with experience building reliable and scalable machine learning infrastructure and a strong desire to contribute to the future of robot navigation for logistics and transportation. About the Work Mainly focus on building and improving HD map generation and release pipelines. Develop scalable workflows to manage first party and third party map data. Develop and manage APIs for internal users to access data. Improve and refactor existing workflows and toolings to boost efficiency. Engage with other mapping teams to help identify issues and establish long-term relationships that include knowledge sharing. About You BS in Computer Science, Robotics or another quantitative area. You have experience in one or more of the following areas: large-scale distributed systems; data storage and processing systems; advanced algorithms using C++ and Python; multithreading; and software performance tuning and optimization. Ability to efficiently develop, debug, and support new technologies in a changing environment. Str

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the role In this role, you will collaborate closely with researchers and engineers on the Learned Behavior teams to tackle plan generation challenges in autonomous driving. You’ll apply state-of-the-art generative modeling techniques—ranging from cutting-edge diffusion, flow matching, energy-based models, and SoTA algorithms—in order to develop novel solutions that generate safe, comfortable, and efficient driving behaviors in the most challenging real world situations. Beyond core research, you’ll own the end-to-end lifecycle of your models, productizing them for robust, real-world autonomous driving deployments on a global scale. About the Work Develop and scale state-of-the-art generative models—especially diffusion architectures, flow-matching techniques, and energy-based models —for autonomous plan generation. Build generative models with foundation models. Leverage large language models and world foundation models for r

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Work Develop and scale state-of-the-art generative models—especially diffusion architectures, flow-matching techniques, and energy-based models —for autonomous plan generation. Build generative models with foundation models. Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation. Optimize generative models using reinforcement learning to improve interactive reasoning. Explore reward modeling/learned verifier using generative models. Explore joint prediction and planning and self-play. Leverage generative models for active learning and world modeling. Develop controllable generative models to guide the generation process towards desired goals, conditions and rewards. Collaborate across autonomy teams while developing holistic solutions to top autonomy challenges. Understand issues, propose ideas, prioritize work and develop solutions to solve them, evaluate

Who We Are Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future. About the Role Nuro is a technology company at the intersection of AI, robotics, and logistics. The Fleet Technician is a specialized technical role responsible for the diagnostic health, software integration, and hardware integrity of Nuro’s autonomous vehicle fleet. This position requires a hybrid mastery of Linux-based systems, hardware-software abstraction layers, and electromechanical engineering to ensure peak operational performance. About the Work Systems Diagnosis & Analysis: Independently analyze and root-cause complex failures involving the interaction between autonomous software stacks and vehicle hardware. Tooling & Automation Development: Design, develop, and implement hardware and software scripts (Python/Bash) to automate fleet health monitoring and optimize vehicle uptime. Deployment & Validation: Execute and validate critical software retrofits, firmware updates, and hardware modifications, ensuring high-fidelity integration with ADAS systems. Process Engineering: Author and standardize Technical Standard Operating Procedures (SOPs) and documentation for cross-functional use by engineering and operations teams. Technical Program Management: Lead specialized fleet-related workstreams, serving as the technical Subject Matter Expert (SME) when collaborating with Software and Hardware Engineering departments. Incident Management: Lead technical resp

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 or Seattle, WA About the Role The Cloudflare Hyperdrive team builds the technology that makes regional databases feel like they are global. Hyperdrive is a core piece of the Cloudflare Developer Platform that accelerates database queries from Cloudflare Workers by pooling connections and caching data at the edge. By eliminating the massive latency overhead of TCP, TLS, and database-specific handshakes, Hyperdrive a