Role Description
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 (strong), 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 (robust — 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 beginning. Since day one, we’ve been
📌 AI Engineer( Mlops ) (Bengaluru)
🏢 UST
📍 Bengaluru