Senior Machine Learning EngineerPhilodesign Technologies Inc • Mumbai, Maharashtra, India

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Senior Machine Learning Engineer

Philodesign Technologies Inc • Mumbai, Maharashtra, India

2 days ago

Job description

Job Title :

Senior MLOps Engineer (Databricks | MLflow | Cloud | PySpark)

Job Function : MLOps

Machine Learning Engineering
Databricks Engineering
Cloud & DevOps
CI / CD Automation

Work Mode & Location :

Location : Ghansoli, Mumbai (Preferred)

Remote flexibility available

Experience : 4–6 years

Budget :

Up to 1 Lakh Per Month (1 LPM)

Job Summary :

We are seeking an experienced Databricks MLOps Engineer to join our Data and AI Engineering team. The ideal candidate should have strong expertise in Databricks, MLflow, cloud platforms, and end-to-end MLOps automation. You will collaborate with data scientists, ML engineers, and business stakeholders to build scalable and reliable production ML pipelines.

Key Responsibilities

1. Databricks Platform Management

Work with Databricks Workspaces, Jobs, Workflows, Unity Catalog, Delta Lake, and MLflow.

Optimize Databricks clusters, compute usage, permissions, and workspace configuration.

2. End-to-End MLOps Lifecycle

Manage model training, versioning, deployment, monitoring, and retraining processes.

Implement deployment strategies including A / B testing, blue-green, and canary releases.

3. Programming & ML Development

Develop ML and data pipelines using Python (pandas, scikit-learn, PyTorch / TensorFlow), PySpark, and SQL.

Maintain code quality through Git, code reviews, and automated tests.

4. Cloud & Infrastructure

Deploy and maintain ML infrastructure across AWS / Azure / GCP.

Implement IaC using Terraform.

Build and manage containerized ML workloads using Docker or Kubernetes.

5. CI / CD & Automation

Create CI / CD pipelines using Jenkins, GitHub Actions, or GitLab CI.

Automate data validation, feature generation, training, and deployment pipelines.

6. Monitoring & Observability

Configure monitoring for data quality, model drift, inference performance, and model health.

Integrate model explainability using SHAP or LIME.

7. Feature Engineering & Optimization

Build and manage definitions in Databricks Feature Store.

Run distributed training and hyperparameter tuning using frameworks such as Optuna or Ray Tune.

8. Collaboration & Documentation

Work along with DS, DE, DevOps, and business teams.

Create detailed documentation for pipelines, processes, and systems.

Mentor junior engineers and support best practices adoption.

Must-Have Skills

Databricks (Core)

MLflow

End-to-End MLOps

Python – pandas, scikit-learn, PyTorch / TensorFlow

PySpark

AWS (SageMaker experience preferred)

Docker / Kubernetes

CI / CD – Jenkins, GitHub Actions, GitLab CI

Location Preference :

Ghansoli, Navi Mumbai candidates preferred.

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Senior Machine Learning Engineer • Mumbai, Maharashtra, India

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