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vLLM Jobs in San Francisco
27 open positions · Updated 4 days ago
27 vLLM roles across 17 companies, most in AI/ML; typical advertised salary $200k
Who is hiring (17 companies)
Role types
Work arrangement: 8 hybrid · 4 on-site · 15 not stated
Advertised salaries: p25 $200k · median $200k · p75 $203.5k (from 15 disclosed annual salaries, USD)
Counts are open roles Joblaze currently tracks on company career pages for this exact skill/location; salaries are advertised minimums, annual, converted to USD.
Showing 20 of 27 positions
Search with filters →Own the GPU cluster infrastructure at Perplexity AI, building a self-serve platform for training and inference workloads.
Join Specter as an ML Infrastructure engineer to build and scale machine learning systems for real-time perception across edge-cloud platforms.
Join Preference Model as a Senior ML Infrastructure Engineer to build scalable infrastructure for post-training research on large language models.
Build inference systems for AI models in production at Gimlet Labs, focusing on performance and efficiency.
Join Inferact as a Member of Technical Staff to manage vulnerability processes for vLLM's AI infrastructure.
Join Inferact as a Forward Deployed Engineer to optimize AI inference systems in customer environments.
Join Handshake as a Senior Software Engineer to build scalable ML infrastructure for a fast-growing AI data business.
Join Inferact as an inference runtime engineer to optimize AI model execution across diverse hardware and architectures.
Join Inferact as a Developer Relations Engineer to shape how developers learn and build with vLLM, the AI inference engine.
Own the inference systems that power frontier AI models in production and research at a tech-first startup.
Join Sesame as an ML Model Serving Engineer to enhance our serving layer for voice agents with cutting-edge techniques.
Join Stuut as a Member of the Technical Staff to design and deploy AI-powered systems for financial operations.
Join Abridge as a Machine Learning Infrastructure Engineer to optimize AI model inference infrastructure in a fast-paced healthcare startup.
Drive the adoption of AI runtime services at CoreWeave, leveraging your expertise in distributed systems and AI infrastructure.