ML/AI Engineer – MLOps / 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.

Work arrangement
No