Machine Learning Engineer (Staff Level)

One of our clients who are a leading provider of Revenue Cycle Management (RCM) for the healthcare industry is 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). Professional 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/tensor parallelism); distributed training experience a plus. Optimization: experience profiling and optimizing code execution and model inference (PTQ/QAT/AWQ/GPTQ), pruning, distillation, KV-cache optimization, Flash Attention. Scalable 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 code. Understanding of the full ML lifecycle: data collection, model training, deployment, inference, optimization, and evaluation. #J-18808-Ljbffr