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/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.