JPMorgan Chase
Lead Machine Learning Engineer-MLOps
$171K–$260K
Palo Alto, CA +1 · Full-time · Posted Jul 1, 2026
- Location
- Palo Alto, CA
New York, NY - Experience
- 6+ years with a BS, or 4+ years with an MS.
- Education
- BS in Computer Science or related Engineering field, or MS degree in Computer Science or related Engineering field.
About the job
Build and operate MLOps infrastructure for recommendation and personalization models, including distributed training, batch and real-time inference, LLM deployment, and model monitoring.
What you'll do
- Build and maintain pipelines for distributed model training and batch/real-time inference.
- Apply quantization and deploy LLMs; manage vector databases and monitoring pipelines.
- Collaborate across teams to develop and improve scalable, reliable ML infrastructure.
What they ask for
- BS in Computer Science or a related Engineering field with 6+ years of experience, or an MS in either field with 4+ years of experience.
- Extensive experience with Python and cloud computing; AWS preferred.
- Knowledge of LLM quantization techniques and experience with systems engineering fundamentals, including CUDA, caching, autoscaling, and high-throughput, low-latency systems.
- Experience with model training and deployment, observability, and big data/ML or training/inference tools such as Ray, DuckDB, Spark, vllm, or SGLang.
Nice to have
- Experience with recommendation and personalization systems.
- Experience with CUDA, containers, Kubernetes or ECS, DAG orchestration, or databases.
Pay
USD $171,000.00-$260,000.00 base salary (Palo Alto, CA); USD $171,000.00-$260,000.00 base salary (New York, NY)
Tools
Python, AWS, CUDA, Ray, DuckDB, Spark, vllm/SGLang, Kubernetes
AI focus
Build and operate recommendation and personalization ML systems; train and serve models, deploy quantized LLMs, and support AI applications with vector databases.
Model-written summary · the original posting is authoritative