Logo for Clera Inc.

Senior Machine Learning Engineer

Role overview

Qualifications

  • 8+ years of professional software engineering and machine learning experience
  • Strong healthcare industry background
  • Deep expertise across the full ML lifecycle
  • Hands-on MLOps experience with strong Python and SQL skills

Responsibilities

  • Design, develop, deploy, and maintain enterprise-scale machine learning solutions
  • Build end-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and retraining
  • Develop and maintain MLOps pipelines including CI/CD, model registry, and automated deployment
  • Monitor production models for drift, accuracy degradation, and overall system health

About the company

Clera Inc. logo

Clera Inc.

Staffing & Recruiting

Clera is an AI talent agent that represents job candidates and connects them directly with hiring managers at venture-backed startups. The platform uses artificial intelligence to match professionals with suitable career opportunities and facilitates introductions via email, iMessage, and WhatsApp, bypassing traditional job application processes.

Company details

IndustryStaffing & Recruiting
Company size11-50

Your match analysis

See how your profile stacks up against this role.

We compared the job requirements to your profile to show where you're strong and where you fall short.

Job description

About the Role

This is a Senior Machine Learning Engineer role embedded within a growing AI and Data Science team at a healthcare-focused data and analytics company. You'll take end-to-end ownership of enterprise-scale ML solutions — from raw data through to production — playing a critical part in delivering compliant, high-impact AI capabilities in a regulated healthcare environment.

What You'll Do

  • Design, develop, deploy, and maintain enterprise-scale machine learning solutions from the ground up.

  • Build end-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and retraining.

  • Develop and maintain MLOps pipelines including CI/CD, model registry, feature stores, automated deployment, and rollback strategies.

  • Monitor production models for drift, accuracy degradation, and overall system health.

  • Develop REST APIs and integrate ML services into enterprise cloud applications.

  • Optimize models for latency, scalability, reliability, and cost.

  • Collaborate cross-functionally with Data Engineers, Software Engineers, Product Managers, and Clinical teams.

  • Provide technical leadership on AI/ML initiatives and ensure compliance with HIPAA, PHI, and PII standards.

What We're Looking For

  • 8+ years of professional software engineering and machine learning experience.

  • Strong healthcare industry background — this is a firm requirement.

  • Deep expertise across the full ML lifecycle: preprocessing, feature engineering, model development, calibration, deployment, monitoring, and maintenance.

  • Hands-on MLOps experience with strong Python and SQL skills.

  • Proficiency with distributed computing (Apache Spark) and Databricks in production environments.

  • Experience with at least one major cloud platform (Azure, AWS, or GCP).

  • Familiarity with MLflow, Feature Stores, Model Registries, Docker, and Git.

  • Experience building and integrating REST APIs; strong debugging and performance-tuning skills.

  • Working knowledge of HIPAA compliance requirements when handling sensitive healthcare data.

  • Nice to have: LLMs in production, RAG/prompt engineering, GenAI, Kubernetes, Scala, or managed ML platforms (Azure ML, SageMaker, Vertex AI).

  • US work authorization required; visa sponsorship is not available.

Compensation & Benefits

Hourly contract rate of $70–$75/hr on W2, equivalent to approximately $145,600–$156,000 annually. This is a contract (W2) engagement. Visa sponsorship is not available.

Location

Based in Palo Alto, CA. Work arrangement details to be confirmed with the hiring team.

Apply once. Then go straight to the hiring manager.

After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.

MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
Unlocked after you apply
·

Machine Learning Engineer Related jobs

Other jobs at Clera Inc.

Premium

Reach out to the hiring manager directly.

Gain access to the contact details of the hiring managers who actually decide, and reach out to network with them directly. That, plus more when you upgrade:

  • Full match report with fit score and gaps
  • Career diagnostics on how recruiters read you
  • Curated company matches and warm intros
  • 48h early access to new roles

Cancel anytime.