Software Engineer- BIS (Baseten Inference Stack)

About BasetenBaseten 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 $300M Series E, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products.THE ROLEBaseten’s Inference Stack team builds the distributed runtime that powers large-scale LLM inference across our platform. We operate at the intersection of distributed systems, model performance, infrastructure, and developer experience. We enable customers to deploy and operate cutting-edge LLM models with industry-leading performance, scalability, reliability, and ease of use.As a Software Engineer on the Inference Stack team, you’ll work across the stack - from the developer experience customers use to deploy models, the libraries used for features like tool calling and reasoning, all the way down to the systems we use to orchestrate deployments in Kubernetes and route traffic efficiently.This is an ideal role for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users.EXAMPLE INITIATIVESBlog Postshttps://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybridResponsibilitiesDevelop infrastructure and orchestration systems for deploying and managing large-scale distributed LLM inferenceWork across the stack, from customer-facing features to low-level infrastructure componentsBuild platform capabilities related to routing, autoscaling, scheduling, observability, and runtime managementImprove the reliability, scalability, and usability of our inference stackCollaborate closely with Model Performance engineers to make new inference optimizations broadly available to customers and easy to configureHelp define best practices around testing, release automation, benchmarking, and operational excellenceDebug complex production systems spanning Kubernetes, distributed runtimes, networking, and GPU workloadsMake thoughtful engineering tradeoffs balancing performance, reliability, operational simplicity, and developer experienceOwn projects end-to-end: from architecture and implementation through deployment, monitoring, and iteration based on customer feedbackRequirementsBachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related fieldStrong background in distributed systems, backend infrastructure, or platform engineeringExperience building and operating production systems where reliability, latency, and scale are first-class concernsStrong sense of developer experience: you think about how systems are used, not just how they workMotivated and willing to learn new languages, frameworks, and systems as neededAbility to debug complex systems across multiple layers of the stackGenuine interest in inference engineering. You don’t need to have hands on experience but are willing to learnExcellent communication and collaboration skillsBONUSExperience with Kubernetes, including concepts like operators and custom resourcesPrior work on Dynamo, vLLM, SGLang, TensorRT-LLM, or similar inference frameworksExperience with distributed scheduling, autoscaling, or service orchestrationExperience operating GPU workloads in productionFamiliarity with observability tooling, CI/CD systems, or release automationExperience contributing to open-source infrastructure or ML systemsBenefitsCompetitive compensation, including meaningful equity. 100% coverage of medical, dental, and vision insurance for employee and dependentsFlexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)Paid parental leaveFertility and family-building stipend through CarrotCompany-facilitated 401(k)Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).Compensation Range: $180K - $360K