Machine Learning Engineer (Staff Level)

One of our clients who are a leading provider of Revenue Cycle Management (RCM) for the healthcare industry are looking to fill "ML Engineer" (various levels - Senior, Lead & Staff) who has experience owning training and/or serving in production at scale.Hybrid role (3 days onsite either from San Jose, CA or Austin, TX)Educational Qualifications:Bachelor's in computer science, Electrical/Computer Engineering, or a related field required; Master’s preferred (or equivalent industry experience).Strong systems/ML engineering with exposure to distributed training and inference optimization.Industry Experience:3–5 years in ML/AI engineering roles owning training and/or serving in production at scale.Demonstrated success delivering high-throughput, low-latency ML services with reliability and cost improvements.Experience collaborating across Research, Platform/Infra, Data, and Product functions.Technical Skills:Familiarity with deep learning frameworks: PyTorch (primary), TensorFlow.Exposure to large model training techniques (DDP, FSDP, ZeRO, pipeline/tensorparallelism); distributed training experience a plusOptimization: experience profiling and optimizing code execution and modelinference: (PTQ/QAT/AWQ/GPTQ), pruning, distillation, KV-cache optimization, Flash AttentionScalable serving: autoscaling, load balancing, streaming, batching, caching;collaboration with platform engineers.Data & storage: SQL/NoSQL, vector stores (FAISS/Milvus/Pinecone/pgvector),Parquet/Delta, object stores.Write performant, maintainable codeUnderstanding of the full ML lifecycle: data collection, model training, deployment, inference, optimization, and evaluation.