Senior Machine Learning Engineer

ABOUT THE ROLE

We are an IT services consultancy placing a Senior Machine Learning Engineer with one of our end clients — a growing healthcare technology organization focused on AI and Data Science. This is a W2 contract engagement ideal for an experienced ML engineer who thrives in fast-paced environments, takes strong ownership of complex initiatives, and has a proven track record building production-grade ML solutions within the healthcare industry.

You will join the client's AI and Data Science team and lead end-to-end machine learning efforts spanning the full model lifecycle — from data preparation and feature engineering through to deployment, monitoring, and optimization — all within a HIPAA-compliant, enterprise-scale environment.

WHAT YOU'LL DO

• Take complete ownership of designing, developing, deploying, and maintaining enterprise-scale machine learning solutions.
• Build end-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and retraining.
• Design scalable, production-ready ML systems with a focus on high availability, performance, and reliability.
• Develop and maintain MLOps pipelines including CI/CD, model registry, feature stores, automated deployment, monitoring, and rollback strategies.
• Monitor production models for model drift, data drift, accuracy degradation, and overall system health.
• Collaborate cross-functionally with Data Engineers, Software Engineers, Product Managers, Clinical teams, and business stakeholders.
• Develop REST APIs and integrate ML services into enterprise cloud applications.
• Optimize models for latency, scalability, reliability, and operational cost.
• Provide technical leadership on AI/ML initiatives across the team.
• Ensure compliance with HIPAA, PHI, PII, and enterprise security standards at all stages of development.

WHAT WE'RE LOOKING FOR

Required Qualifications

• 8+ years of professional software engineering and machine learning experience.
• Strong healthcare industry experience is mandatory; demonstrated ability to work with sensitive healthcare data under HIPAA and related compliance frameworks.
• Full ML lifecycle expertise: data preprocessing, feature engineering, model development, calibration, deployment, monitoring, and maintenance.
• Hands-on MLOps experience with a strong ownership mindset.
• Proficiency in Python and SQL.
• Experience with distributed computing (Apache Spark) and Databricks in production environments.
• Practical experience with major cloud platforms: Azure, AWS, and/or GCP.
• API development and integration skills; strong debugging and performance-tuning capabilities.
• Excellent communication skills for collaborating with technical and non-technical stakeholders.

Required Technical Skills

• Python, SQL, Machine Learning, MLOps
• Databricks, Apache Spark, MLflow
• Feature Store, Model Registry
• CI/CD Pipelines, REST APIs
• Git, Docker; Kubernetes (preferred)
• Azure / AWS / GCP

Preferred / Nice-to-Have

• LLMs in production; prompt engineering, RAG, and GenAI experience.
• Scala proficiency.
• Managed ML platform experience: Azure ML, Amazon SageMaker, and/or Google Vertex AI.
• Experience designing HIPAA-compliant AI solutions and distributed ML architectures.

COMPENSATION & BENEFITS

• Rate: $70–75/hr on W2 (contract engagement).
• Visa Sponsorship: Not available — US work authorization required.

LOCATION

Based in Palo Alto, CA. On-site / hybrid arrangement at the client's location.