ML Engineer I
Who we are:
At UST, we help the world’s best organizations grow and succeed through transformation. Bringing together the right talent, tools, and ideas, we work with our client to co-create lasting change. Together, with over 30,000 employees in 25 countries, we build for boundless impact—touching billions of lives in the process. Visit us at .
The Opportunity:
• Build end-to-end pipelines — data ingestion, training, evaluation, packaging, versioning, and deployment.
• Develop and maintain Jenkins CI/CD for Dev → QA → Production promotion with multi-stage gates.
• Deploy model-serving APIs on AKS using FastAPI and vLLM; apply ONNX/TensorRT optimizations.
• Set up observability — drift detection (Evidently AI), Prometheus/Grafana, Azure Monitor.
• Apply DevSecOps practices — Key Vault, Managed Identity, SonarQube, Trivy/Snyk.
• Application Development – REST, WebSocket Frameworks using FastAPI
What are we Looking for:
· • 4+ years in ML/AI engineering or DevOps with hands-on production MLOps pipeline experience.
• CI/CD tooling: CI tooling (UV, Ruff,
Pyrefly), Jenkins (solid), Azure DevOps, GitOps concepts; Git and pre-commit workflows.
• Databricks ML pipelines (Delta Lake, Workflows, MLflow), Asset Bundles and PySpark for data processing.
• Model serving: FastAPI, Docker, AKS; exposure to vLLM and ONNX/TensorRT optimization.
• Python (strong — FastAPI, Pydantic, async), Bash, YAML/SQL scripting.
• Cloud knowledge – Azure/AWS/GCP Storage, AI related services.
• Databases and storage: PostgreSQL, Redis, ADLS Gen2.
• Understanding of containerization, Helm, and infrastructure automation.
· Nice to Have
• Airflow, DVC, and experiment tracking (W&B; / Comet ML).
• Terraform, KEDA, Azure APIM, and AAD RBAC configuration.
• LLM fine-tuning pipelines; Ray Serve or BentoML exposure.
• Groovy (Jenkinsfile).
• Manufacturing or semiconductor domain experience.
What we believe:
We’re proud to embrace the same values that have shaped UST since the beginni
📌 AI Engineer( Mlops ) (Bengaluru)
🏢 UST
📍 Bengaluru