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HCLTech

Senior Technical Lead

Bengaluru · Senior

Good timing - competition is buildingVerified listingPosted 5d ago

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64Skills
97Experience

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Skills required

38 listed
CI/CDAzure MonitorAzure DevOpsMLOps (Machine Learning Operations)Artificial Intelligence Markup Language (AIML)JenkinsApplication Programming Interface (API)ONNX (Open Neural Network Exchange)+30 more
CI/CDAzure MonitorAzure DevOpsMLOps (Machine Learning Operations)Artificial Intelligence Markup Language (AIML)

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Job description

Job Summary

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

Skill Requirements

• 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.

Other Requirements

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All open roles at HCLTechAll Machine Learning Engineer jobs in Bengaluru

Two ways in

Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreFree · sign in
86Overall
64Skills
97Experience

Your score for this role already exists

ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

Always free · no credit card · 1 tap with Google

Free · no signup

Get tomorrow's jobs before you have to search

Daily job drops, skill trends and free resources - posted straight to the group. Leave any time.

Join WhatsAppJoin Telegram

No spam. Just jobs and resources.

Why people use ASAI

Someone shared one job with you. ASAI keeps finding the rest.

  • Scored, not searched. Every role ranked against your actual profile.

  • Alerts as often as hourly. Reach new roles while the pile is still small.

  • Skill gaps, spelled out. See exactly which requirements you don't meet yet.

  • Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

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