5-7 years of experience in AI/ML product development or infrastructure with a focus on performance and scalability.
Technical background in software engineering or ML engineering, with hands-on experience.
Strong grasp of model serving architectures and tradeoffs in latency, throughput, quality, and cost.
Experience collaborating with researchers or engineers to implement complex capabilities in production.
Rigorous approach to benchmarking and performance measurement.
Ability to translate technical advancements into customer value.
Responsibilities
Collaborate with inference engineering and research teams to deliver new performance capabilities.
Translate technical advancements into practical product features for customers.
Define benchmarks to showcase improvements in latency, throughput, and cost.
Analyze customer workloads to prioritize impactful optimizations.
Simplify the configuration and adoption of performance features in production.
Educate customers on tradeoffs related to hardware and model configurations.
Coordinate with engineering on release readiness and testing for customer trust.
Benefits
Competitive compensation with equity options.
100% coverage of medical, dental, and vision insurance for employees and dependents (U.S. only).
Flexible PTO policy, including a company-wide Winter Break.
Paid parental leave.
Fertility and family-building stipend through Carrot.
Company-facilitated 401(k) (U.S. only).
Exposure to various ML startups for learning and networking opportunities.
Full Job Description
THE ROLE
Make AI inference faster, smarter, and more efficient at scale.
Making AI models faster and cheaper is one of the most important engineering challenges in the industry. But a faster runtime alone isn't enough. Customers need to understand what improved, whether it works for their models, and how to take advantage of it in production.
We're looking for a deeply technical Product Manager to work alongside our inference engineers and researchers, turning advances in model serving and performance into capabilities customers can confidently adopt.
You'll help bridge the gap between cutting-edge systems engineering and real-world production workloads.
RESPONSIBILITIES
Work with inference engineering and research teams to bring new performance capabilities to customers.
Translate advances in batching, caching, quantization, speculative decoding, and serving architectures into useful product features.
Define benchmarks and evaluations that demonstrate meaningful improvements in latency, throughput, quality, and cost.
Understand customer workloads and help prioritize the optimizations that will have the greatest impact.
Make performance features easier to configure, evaluate, and adopt in production.
Help customers understand tradeoffs across hardware, model configurations, autoscaling, and routing.
Partner with engineering on release readiness, compatibility, and regression testing so customers can trust new capabilities.
REQUIREMENTS
Experience building and shipping AI/ML products or infrastructure, particularly where performance, scalability, or production behavior mattered.
A technical background in software engineering, ML engineering, research, or equivalent hands-on experience.
Strong understanding of model serving architectures, GPU economics, and latency, throughput, quality, and cost tradeoffs.
Experience working closely with researchers or infrastructure engineers to bring technically complex capabilities into production.
A rigorous approach to benchmarking, experimentation, and performance measurement.
Strong product judgment and the ability to translate deep technical work into clear customer value.
NICE TO HAVE
Hands-on experience with PyTorch, vLLM, TensorRT-LLM, SGLang, NVIDIA Dynamo, or similar technologies.
Experience with open-source inference projects, model optimization, or ML systems research.
WHAT SUCCESS LOOKS LIKE
Customers can take advantage of Baseten's latest inference optimizations without becoming experts in the underlying runtime. Performance improvements translate into measurable gains in speed, reliability, and cost for real production workloads.
BENEFITS
Competitive compensation, including meaningful equity
(U.S. only) 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
(U.S. only) 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.
