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

GHR Healthcare · Anywhere

Full-timeSeniorPythonAWSAzureDockerKubernetesPyTorchTensorFlowLangChain

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About the Role

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 productionMust have experience working with sensitive, regulated, or compliance-driven data environmentsNo third-party submissions / no C2CWhat You'll Be DoingDesign 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 datasetsBuild scalable, production-ready services using modern cloud infrastructurePartner with stakeholders to translate real business problems into ML solutionsImplement model monitoring, drift detection, and retraining strategiesWhat We're Looking For5+ 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 RoleWork on real-world ML systems at scaleHigh visibility, high impact workCollaborative, engineering-focused team100% remotePermanent / direct hireSalary: $135,000 – $150,000

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