Senior Machine Learning Engineer

Clera; Palo Alto (CA); Hybrid; USD 96,000 - 103,000; Full time

Job summary

Clera in Palo Alto, CA seeks a Senior Machine Learning Engineer for a W2 contract with a healthcare technology client. You will own end-to-end ML solutions, build production ML pipelines, and lead MLOps practices, including CI/CD, model registry, feature stores, and monitoring.

You will ensure HIPAA compliance and collaborate with data engineers, software engineers, product managers, and clinical teams. The role requires 8+ years of ML and software experience, strong Python/SQL,

Qualifications

• 8+ years of professional software engineering and machine learning experience.
• Strong healthcare industry experience is mandatory; ability to work with sensitive healthcare data under HIPAA.
• 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.

Responsibilities

• 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.

Skills

Years of experience

Healthcare domain experience

ML lifecycle expertise

MLOps ownership

Python

SQL

Apache Spark

Databricks

Azure

AWS

GCP

API development

Communication

Tools

Databricks

Apache Spark

MLflow

Feature Store

Model Registry

CI/CD Pipelines

REST APIs

Git

Docker

Kubernetes

Job description

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.

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.