Senior Machine Learning Engineer
Senior Machine Learning Engineer
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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:
- Bachelors or Masters 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
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
