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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 As an Engineering Manager (Player & Coach), you will lead and mentor a team of Forward Deployed Engineers focused on building, scaling, and optimizing LLM inference workloads for Baseten customers. Applying both hands-on technical ownership and managerial leadership, you will guide your team through the processes of designing, deploying, and managing high performance, low latency AI applications on Baseten’s platform. FDE at Baseten is not a sales function – we are a mix of engineering, product, and customer architects who contribute to the core Baseten codebase, drive large portions of our feature roadmap, and execute on complicated customer engagements. You will also partner with product, infrastructure, and other customer engineering teams to ensure that large language models (LLMs) and other generative AI systems deliver best-in-class performance, reliability, and cost efficiency in production environments. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Leadership & Team Management Lead, mentor, and grow a team of Forward Deployed Engineers, providing guidance on technical direction, project execution, and professional deve

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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 Anyscale is looking for a Software Engineer to join the Platform and Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the team, we build the scalable, secure, and robust backbone that enables this vision, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world. Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads. We are seeking a talented Software Engineer with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale's cloud platform. You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impa

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 As a Distributed LLM Inference Engineer, you will help systems and optimizations that push the boundaries of performance for inference at large scale. This is an incredibly critical role to Anyscale as it allows us to achieve a market leading position for AI infrastructure. As part of this role, you will Iterate very quickly with product teams to ship the end to end solutions for Batch and Online inference at high scale which will be used by open-source Ray users and customers of Anyscale Work across the stack integrating Ray Data and LLM engine providing optimizations achieving low cost solutions for large scale ML inference Integrate with Open source software like vLLM, work closely with the community to adopt these techniques in Anyscale solutions, and also contribute improvements to open source Follow the latest state-of-the-art in the open source and the research community, implementing and extending best practices We'd love to hear from you if you have Familiarity with running ML inference at large scale with high throughput and low latency Familiarity with deep learning and deep learning frameworks (e.g. PyTorch) Solid understanding of distributed systems, ML inference challenges Bonus points