대규모 LLM 추론을 위한 분산 런타임과 인프라를 설계하고 운영해요. 고객이 모델을 배포하는 개발자 경험부터 쿠버네티스 기반의 오케스트레이션까지 전체 스택을 다뤄요. 컴퓨터 공학 관련 학위가 필요하며, 분산 시스템이나 백엔드 인프라 운영 경험을 갖춰야 해요. 추론 엔지니어링에 대한 관심이 필수적이지만, 관련 실무 경험이 없어도 학습 의지가 있다면 지원할 수 있어요.
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.
Baseten’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.
Blog Posts
https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/
https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/
Develop infrastructure and orchestration systems for deploying and managing large-scale distributed LLM inference
Work across the stack, from customer-facing features to low-level infrastructure components
Build platform capabilities related to routing, autoscaling, scheduling, observability, and runtime management
Improve the reliability, scalability, and usability of our inference stack
Collaborate closely with Model Performance engineers to make new inference optimizations broadly available to customers and easy to configure
Help define best practices around testing, release automation, benchmarking, and operational excellence
Debug complex production systems spanning Kubernetes, distributed runtimes, networking, and GPU workloads
Make thoughtful engineering tradeoffs balancing performance, reliability, operational simplicity, and developer experience
Own projects end-to-end: from architecture and implementation through deployment, monitoring, and iteration based on customer feedback
Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related field
Strong background in distributed systems, backend infrastructure, or platform engineering
Experience building and operating production systems where reliability, latency, and scale are first-class concerns
Strong sense of developer experience: you think about how systems are used, not just how they work
Motivated and willing to learn new languages, frameworks, and systems as needed
Ability to debug complex systems across multiple layers of the stack
Genuine interest in inference engineering. You don’t need to have hands on experience but are willing to learn
Excellent communication and collaboration skills
Experience with Kubernetes, including concepts like operators and custom resources
Prior work on Dynamo, vLLM, SGLang, TensorRT-LLM, or similar inference frameworks
Experience with distributed scheduling, autoscaling, or service orchestration
Experience operating GPU workloads in production
Familiarity with observability tooling, CI/CD systems, or release automation
Experience contributing to open-source infrastructure or ML systems
Competitive compensation, including meaningful equity.
100% coverage of medical, dental, and vision insurance for employee and dependents
Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
Paid parental leave
Fertility and family-building stipend through Carrot
Company-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).
