TI
MLOps Technical Lead
Tranzeal Inc.
🇮🇳 India
On-site
Staff / Principal
3 weeks ago
- MLOps
- AI
- Devops
- AI/ML
- Machine Learning
- CI/CD
- Jenkins
- AKS
- FastAPI
- vLLM
- ONNX
- TensorRT
- Prometheus
- Grafana
- Azure Monitor
- DevSecOps
- Key Vault
- SonarQube
- Trivy
- Snyk
- Azure DevOps
- ArgoCD
- GitOps
- Databricks
- Delta Lake
- MLflow
- Unity Catalog
- Airflow
- PySpark
- Helm
- Docker
- Azure
- Terraform
- RBAC
- Python
- Pydantic
- Groovy
- Bash
- YAML
- SQL
- PostgreSQL
- Redis
- Ray
- Weights & Biases
3 weeks ago
Location : ITPL, Bengaluru
work mode : 4 days work from office
Interview: AMAT interview will face to face - need local candidates
Experience Required: 8+ years
Salary : 28 LPA
Open New Demand # AMDIA00247 - AI Engineer + ML ops - Lead - 1
MLOps Technical Lead
Snapshot
Experience: 8+ years in ML/AI engineering or DevOps (incl. 4+ yrs production MLOps)
Report To: Manager, AIML
Education: Master's (preferred) or Bachelor's in CS, Software Engineering, or Data Science
About the Role
Own the complete MLOps backbone for AI/ML and GenAI solutions — from model packaging and CI/CD delivery through production monitoring. Bridge data-science experimentation and enterprise-scale deployment and set engineering standards for the Enterprise AI MLOps practice.
Key Responsibilities
• Design end-to-end pipelines — ingestion, training, evaluation, packaging, versioning, deployment, and monitoring.
• Own Jenkins CI/CD (Declarative/Scripted) for Dev → QA → Production with multi-stage gates.
• Deploy model-serving APIs on AKS (FastAPI, vLLM); apply ONNX/TensorRT and blue/green rollouts.
• Build observability stacks — drift detection (Evidently AI), Prometheus/Grafana, Azure Monitor.
• Enforce DevSecOps — zero-credential pipelines via Key Vault + Managed Identity, SonarQube, Trivy/Snyk.
• Set MLOps engineering standards and mentor engineers across the practice.
Must-Have Skills
• 7+ years in ML/AI engineering or DevOps with 4+ years operating production MLOps pipelines.
• CI/CD & Dev tooling: Jenkins (expert), Azure DevOps, ArgoCD (GitOps); UV, Ruff, Pyrefly, pre-commit.
• MLOps & data: Databricks end-to-end (Delta Lake, Workflows, MLflow, Unity Catalog), Airflow, DVC, PySpark.
• Serving & infra: FastAPI, ONNX/TensorRT, AKS, Helm, Docker, KEDA, Azure APIM, Terraform.
• Security: Key Vault, AAD RBAC, Managed Identity; zero-credential pipeline design
• Languages: Python (expert — FastAPI, Pydantic, async), Groovy (Jenkinsfile), Bash, YAML/SQL.
• Databases & storage: PostgreSQL, Redis, ADLS Gen2.
• A/B testing and canary/shadow deployment experience.
• Proven technical leadership, mentoring, and stakeholder communication.
Nice to Have
• LLM fine-tuning pipelines and large-scale model-serving optimization.
• Ray Serve, BentoML for advanced model serving patterns.
• Experiment tracking and governance (W&B / Comet ML, Unity Catalog policies).
• Multi-cloud or hybrid deployment strategy and cost optimization.
• Semiconductor or manufacturing domain experience.
MLOps Technical Lead · Tranzeal Inc.