ML Engineer

Posted on April 15, 2025

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Job Description

  • Experience: 4+ years
  • Location: Bagmane World Technology Center, Bengaluru
  • Mandatory Skills: ML Engineering, MLOPS, Python Development, OOPs concept, Optimization, Code Deployment, MLOPS, DevOps, API Integration, Knowledge of Azure, Git
  • We are looking for a highly skilled Machine Learning Engineer with a solid foundation in Python, ObjectOriented Programming (OOP), and experience in deploying ML models into production environments.
  • The ideal candidate should have expertise in model optimization, API integration, and hands-on exposure to DevOps/MLOps workflows on cloud platforms, especially Microsoft Azure.
  • Responsibilities:
  • 1. Design, develop, and deploy scalable ML models for production use-cases.
  • 2. Implement and optimize model training pipelines, validation workflows, and inference pipelines.
  • 3. Collaborate with data scientists, software engineers, and DevOps teams to integrate ML solutions with backend services and APIs.
  • 4. Build CI/CD pipelines for automated deployment and monitoring of models.
  • 5. Ensure version control and collaboration through Git-based workflows.
  • 6. Implement best practices in MLOps: model versioning, reproducibility, rollback strategies. 7. Optimize code for performance, scalability, and maintainability.
  • 8. Integrate ML systems with cloud services (preferably Azure) and external APIs.
  • 9. Participate in code reviews and mentoring junior engineers on clean coding principles.
  • Requirements:
  • 1. Advanced proficiency with clean, modular code and scripting
  • 2. Strong grasp of object-oriented design principles
  • 3. End-to-end model building, tuning, evaluation, deployment
  • 4. Model and code optimization for low-latency inference
  • 5. Model lifecycle management, monitoring, CI/CD in ML pipelines
  • 6. Familiarity with tools like Docker, Kubernetes, Jenkins
  • 7. RESTful API development and consumption
  • 8. Experience with Azure ML, Blob Storage, DevOps pipelines
  • 9. Branching strategies, merge/rebase, pull requests, GitOps
  • 10. Bachelor�s or Master�s degree in Computer Science, Data Science, Engineering, or a related field
  • Nice-to-Have Skills:
  • 1. Exposure to containerization and orchestration tools (e.g., Docker, Kubernetes)
  • 2. Experience with Azure DevOps, Terraform, or similar IaC tools
  • 3. Familiarity with feature stores, data versioning tools (like DVC)
  • 4. Knowledge of monitoring tools for ML systems (e.g., Prometheus, Grafana)

Required Skills

ml mlops engineer