Senior Machine Learning Engineer

1 Month ago • 5 Years + • Research Development

Job Summary

Job Description

TRIARQ Health is seeking an experienced Machine Learning Engineer to lead the development and deployment of ML models for intelligent products. This role involves collaborating with Data Science, Engineering, and Product teams to build scalable and efficient solutions. The engineer will architect, build, and maintain end-to-end ML systems, develop and optimize models for various use cases, and implement MLOps best practices. Responsibilities also include evaluating and monitoring model performance, ensuring robustness, fairness, and explainability, and documenting processes. Experience with healthcare data and NLP models applied to clinical documentation is preferred.
Must have:
  • Bachelor's or Master's degree in CS, ML, Data Science, or related
  • 5+ years of hands-on experience in ML engineering or applied data science
  • Strong Python and ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost)
  • Experience deploying ML models in production (Docker, Kubernetes, AWS/GCP/Azure)
  • Familiarity with MLOps tools (MLflow, DVC, Kubeflow)
  • Proficient in building ETL/ELT pipelines and handling large datasets
  • Strong understanding of statistical methods and model evaluation
  • Good software engineering practices (version control, testing, CI/CD)
Good to have:
  • Exposure to healthcare datasets (EHR, claims, HL7, FHIR)
  • Experience with NLP models for clinical documentation
  • Understanding of HIPAA compliance and PHI handling
  • Contributions to open-source ML projects or publications
  • Experience in regulated industries or mission-critical environments

Job Details

Company Description

TRIARQ Health is a Physician Practice Services company that partners with doctors to run modern patient-centered practices so they can be rewarded for delivering high-value care. TRIARQ’s Physician-led partnerships simplify practices’ transition to value-based care by combining our proprietary, cloud-based practice, care management technology platform, and patient engagement services to help doctors focus on better outcomes.  

Job Description

TRIARQ Health is looking for an experienced Machine Learning Engineer to lead the development and deployment of ML models that power intelligent products and insights. You will collaborate with teams across Data Science, Engineering, and Product to build solutions that are scalable, efficient, and impactful. Candidates with exposure to the healthcare domain are encouraged to apply, although this is not a mandatory requirement. We are looking for an experienced Machine Learning Engineer to lead the development and deployment of ML models that power intelligent products and insights. You will collaborate with teams across Data Science, Engineering, and Product to build solutions that are scalable, efficient, and impactful. Candidates with exposure to the healthcare domain are encouraged to apply, although this is not a mandatory requirement.

Key Responsibilities:

  • Architect, build, and maintain end-to-end ML systems — from data pipelines to model deployment.
  • Develop and optimize machine learning models for use cases such as classification, prediction, recommendation, NLP, or computer vision.
  • Implement MLOps best practices for model training, tracking, deployment, and monitoring.
  • Collaborate with data scientists and domain experts to productionize prototypes and research.
  • Evaluate and monitor model performance; ensure robustness, fairness, and explainability.
  • Document architecture and processes; contribute to knowledge sharing and code reviews.
  • (Preferred) Work with EHR data, claims data, clinical notes, or healthcare interoperability formats like HL7 or FHIR, if applicable.

Qualifications

Required Skills & Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related discipline.
  • 5+ years of hands-on experience in ML engineering or applied data science.
  • Strong command of Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost).
  • Experience deploying ML models in production using containerization (Docker, Kubernetes) and cloud platforms (AWS/GCP/Azure).
  • Familiarity with MLOps tools like MLflow, DVC, or Kubeflow.
  • Proficient in building ETL/ELT pipelines and handling large-scale datasets.
  • Strong understanding of statistical methods, model evaluation metrics, and optimization techniques.
  • Good software engineering practices (version control, testing, CI/CD).

 

    Additional Information

    Preferred Qualifications:

    • Exposure to healthcare datasets such as medical claims, EHR/EMR, HL7, FHIR, or medical coding (CPT, ICD-10).
    • Experience with NLP models applied to clinical documentation or unstructured medical data.
    • Understanding of HIPAA compliance, data anonymization, and PHI handling.
    • Contributions to open-source ML projects or peer-reviewed publications.
    • Experience working in regulated industries or mission-critical environments.

    Location: Nashik, Pune, Navi Mumbai
    Department: AI & ML Engineering
    Experience Level: 5+ years

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