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Zorba AI

AI Engineer + ML ops

Zorba AI

Maharashtra, India
Full-Time
Posted 9 days ago

Job Description & Responsibilities

MLOps Engineer / Developer

Snapshot

Experience: 4–6 years in ML/AI engineering or DevOps

Reports To: MLOps Technical Lead / Manager, AIML

Education: B.E./B.Tech in CS, Software Engineering, or Data Science

About The Role

Build and operate the MLOps pipelines that take AI/ML and GenAI models from experimentation to production — packaging, CI/CD delivery, model serving, and monitoring. A hands-on engineering role bridging data science and enterprise deployment.

Key Responsibilities

  • 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

Must-Have Skills

  • 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 (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.

Skills: azure,ml,data science,fastapi,pipelines

Required Skills

PythonAWSAzureGCPDockerSQLRedisGitCI/CDTerraform

Job Details

Employment TypeFull-Time
Work ModeOn-Site
Experience4 – 6 years
Positions1

Posted by

N/A

Posted on:

29 Sept 2026

About Zorba AI

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