MLops Engineer

6 days ago

Pune, Maharashtra, India DeetsDigital Full time ₹ 8,00,000 - ₹ 24,00,000 per year

Job Description:

  • Design, develop, and maintain
    end-to-end MLOps pipelines
    for training, testing, and deploying ML models at scale.
  • Implement and optimize
    CI/CD workflows using GitHub Actions
    for ML model integration and delivery.
  • Work extensively on
    Databricks
    for model training, orchestration, and deployment.
  • Automate data ingestion, feature engineering, and ML model retraining workflows.
  • Monitor model performance in production and enable automated re-training or alerting mechanisms.
  • Experience with code versioning tools like GitHub, Gitlab, SVC, etc.
  • Ensure ML systems follow
    best practices in version control, reproducibility, and scalability
    .
  • Collaborate with cross-functional teams (Data Scientists, Engineers, Product Managers) to align business objectives with ML solutions.
  • Implement security, compliance, and governance standards for ML pipelines.

Must-Have Skills

  • Databricks
    (MLflow, Delta Lake, Model Registry, Unity Catalog).
  • GitHub CI/CD pipelines
    (bare minimum requirement).
  • Proficiency in
    Python
    and ML-related frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
  • Strong understanding of
    cloud platforms
    (AWS / Azure / GCP) with ML services integration.
  • Experience with
    containerization & orchestration
    (Docker, Kubernetes).
  • Knowledge of
    data engineering workflows
    and distributed data processing (Spark preferred).

Good-to-Have Skills

  • Experience with
    Terraform / Infrastructure as Code (IaC)
    for environment setup.
  • Monitoring tools (Prometheus, Grafana, Datadog, or equivalent).
  • Knowledge of
    feature stores
    and real-time inference pipelines.
  • Exposure to
    data governance, security, and compliance frameworks
    .

Qualifications

  • Bachelor's or master's degree in computer science, Data Engineering, or a related field.
  • 3–6 years of experience in MLOps, DevOps, or Data Engineering with ML focus.

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