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Posted April 22, 2026, closed May 30, 2026. Check out similar open roles below.

Senior Machine Learning Engineer (GenAI / Production Systems) – 100% Remote | Direct Hire

GHR Healthcare
Washington, US
Remote

Who this role is best for

Best suited to senior machine learning engineers with production deployment experience in regulated data environments who thrive in remote settings.

Best fit for

  • Engineers with proven experience deploying ML systems in regulated industries.
    — “Must have experience working with sensitive, regulated, or compliance-driven data environments”
  • Candidates who have built and scaled GenAI solutions beyond prototypes.
    — “Develop and deploy LLM / GenAI solutions (RAG, NLP, prompt engineering, vector search)”
  • Professionals comfortable with full-stack ML pipeline ownership.
    — “Design and build end-to-end ML pipelines (data ingestion → feature engineering → model training → deployment → monitoring)”

Things to consider

  • No C2C arrangements are permitted for this role.
    — “No third-party submissions / no C2C”
  • Resumes must include specific production ML case studies.
    — “A production ML system you built and deployed (what problem it solved, scale, tools used)”

How to stand out

  • Quantify impact metrics for your deployed ML systems.
    — “real-world systems that require scalability, reliability, and measurable business impact”
  • Detail your approach to model monitoring in production.
    — “Implement model monitoring, drift detection, and retraining strategies”
  • Highlight cross-functional collaboration in regulated environments.
    — “Partner with stakeholders to translate real business problems into ML solutions”
Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Deployed production ML systems
  • Implemented GenAI solutions
Typical background
5+ years of experience as a Machine Learning EngineerExperience with regulated data environments

Skills & requirements

Required

PythonTensorFlowPyTorchscikit-learnML PipelinesCloud PlatformsContainerizationGenai / Llms

Preferred

RAGLangchain

Stack & domain

PythonTensorFlowPyTorchscikit-learnAWSAzureGoogle Cloud PlatformDockerKubernetesLangchain

About the role

This role involves designing and deploying machine learning systems that solve real-world business problems, requiring a candidate who is both technically proficient and adept at working in a regulated data environment.

Original posting from GHR Healthcare

We are seeking a Senior Machine Learning Engineer to join a high-impact, enterprise AI initiative focused on building production-grade machine learning and generative AI systems in a complex, data-rich environment.

This is a full-time, direct hire position (no C2C) working on real-world systems that require scalability, reliability, and measurable business impact—not experimental or research-only work.

  • Must have hands-on experience building and deploying ML systems in production
  • Must have experience working with sensitive, regulated, or compliance-driven data environments
  • No third-party submissions / no C2C

What You’ll Be Doing

  • Design and build end-to-end ML pipelines (data ingestion → feature engineering → model training → deployment → monitoring)
  • Develop and deploy LLM / GenAI solutions (RAG, NLP, prompt engineering, vector search)
  • Work with large, complex structured and unstructured datasets
  • Build scalable, production-ready services using modern cloud infrastructure
  • Partner with stakeholders to translate real business problems into ML solutions
  • Implement model monitoring, drift detection, and retraining strategies

What We’re Looking For

  • 5+ years of experience as a Machine Learning Engineer (not just Data Scientist/Analyst)
  • Strong experience with Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
  • Hands-on experience with:
  • ML pipelines / MLOps (CI/CD, model deployment, monitoring)
  • Cloud platforms (AWS, Azure, or Google Cloud Platform)
  • Containerization (Docker, Kubernetes preferred)
  • Experience with GenAI / LLMs (RAG, embeddings, vector databases, LangChain, etc.)
  • Experience working with regulated or high-sensitivity data environments (financial, healthcare, gov, etc.)
  • Strong communication skills and ability to work cross-functionally

🚫 To Be Considered, Please Include:

(Resumes without this will NOT be reviewed)

In your resume or submission, briefly describe:

  • A production ML system you built and deployed (what problem it solved, scale, tools used)
  • A GenAI / LLM use case you’ve implemented (RAG, NLP, etc.)
  • The type of data environment you worked in (regulated, high-compliance, etc.)

Why This Role

  • Work on real-world ML systems at scale
  • High visibility, high impact work
  • Collaborative, engineering-focused team
  • 100% remote
  • Permanent / direct hire
  • Salary: $135,000 – $150,000

Source: GHR Healthcare careers

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