AI ML Ops Engineer
Tarento (company site, opens in a new tab)3–5 yrsIndoreOn-siteDirect career pageEst. 10–18 LPA
Posted on 25 Sept
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Job description
Structured overview of role & requirements
About This Role
- Own deployment, monitoring, and scaling of ML models and pipelines in production environments.
- Build and maintain automated CI/CD pipelines for ML model training, testing, and deployment.
- Manage containerized model-serving infrastructure using Docker and Kubernetes at scale with model performance and system health monitoring.
Minimum Requirements
- 3-5 years of relevant experience in AI/ML Ops or related roles.
- Mandatory skills include Docker, Kubernetes, Python, CI/CD tooling, and cloud infrastructure experience (AWS/Azure/GCP).
- B.E/B.Tech degree required.
- Work mode is hybrid based in Indore.
Ideal Candidate Profile
- Experienced in scalable GPU/cloud infrastructure management and production ML model serving frameworks like Triton Inference Server.
- Skilled in model versioning, experiment tracking tools (MLflow, DVC, Weights & Biases) and monitoring tools (Prometheus, Grafana).
- Strong Linux, networking, debugging fundamentals and familiarity with deploying low-latency AI inference services especially LLM/NLP is advantageous.