ML/AI Engineering or DevOps

About the job Role: ML/AI Engineering or DevOps

Experience: 4–6 Years

Employment Type: Full-time

Location: Bangalore

Company: Pradha Solutions Pvt Ltd

We are looking for an experienced ML/AI Engineer with strong MLOps and DevOps expertise to join our team. The ideal candidate will have hands-on experience building and managing production ML pipelines, model deployment, CI/CD, cloud infrastructure, and scalable AI/ML systems.

Key Responsibilities

• Design, build, and maintain production-grade MLOps pipelines for ML/AI applications.
• Develop and manage CI/CD workflows using Jenkins, Azure DevOps, Git, pre-commit, and modern CI tooling.
• Build and maintain Databricks ML pipelines using Delta Lake, Workflows, MLflow, Asset Bundles, and PySpark.
• Deploy and serve ML models using FastAPI, Docker, and AKS.
• Work on model optimization and deployment using technologies such as ONNX/TensorRT.
• Develop automation and infrastructure workflows using Python, Bash, YAML, and SQL.
• Work with cloud services across Azure, AWS, and GCP, particularly storage and AI/ML related services.
• Manage databases and storage solutions including PostgreSQL, Redis, and ADLS Gen2.
• Implement containerization, Helm, and infrastructure automation practices.
• Collaborate with Data Scientists, ML Engineers, DevOps Engineers, and other stakeholders to deliver scalable ML solutions.

 Must-Have Skills

• 4+ years of experience in ML/AI Engineering, MLOps, or DevOps with hands-on production MLOps experience.
• Strong experience with Python, including FastAPI, Pydantic, and asynchronous programming.
• Experience with Jenkins, Azure DevOps, GitOps, Git, and pre-commit workflows.
• Hands-on experience with Databricks, Delta Lake, MLflow, Workflows, Asset Bundles, and PySpark.
• Experience with FastAPI, Docker, and Kubernetes/AKS for model serving.
• Good understanding of Azure/AWS/GCP cloud environments and AI-related services.
• Experience with PostgreSQL, Redis, and ADLS Gen2.
• Strong understanding of containerization, Helm, and infrastructure automation.
• Good scripting experience with Bash, YAML, and SQL.

 Nice to Have

• Experience with Apache Airflow, DVC, W&B, or Comet ML.
• Knowledge of Terraform, KEDA, Azure APIM, and Azure AD RBAC.
• Experience with LLM fine-tuning pipelines.
• Exposure to Ray Serve or BentoML.
• Experience with Groovy/Jenkinsfile.
• Experience in the manufacturing or semiconductor industry.