Establishes and operates the ML platform, CI/CD/CT pipelines, and infrastructure that enable reliable training, deployment, and monitoring of ML models for the POD.

Key Responsibilities

- Build CI/CD/CT pipelines for automated model training, testing, and deployment.

- Manage ML platform infrastructure (Azure ML, Kubeflow, MLflow, or similar).

- Implement model registry, versioning, and reproducibility practices.

- Monitor model performance, data/model drift, and infrastructure health in production.

Skills and Experience

- 7+ years of experience in MLOps, DevOps, or ML platform engineering roles.

- Hands-on experience building CI/CD/CT pipelines for automated model training, testing, and deployment.

- Proven experience managing ML platform infrastructure such as Azure ML, Kubeflow, MLflow, or similar tooling.

- Experience implementing model registry, versioning, and reproducibility practices.

- Strong Python skills and familiarity with ML frameworks (eg, PyTorch, TensorFlow, scikit-learn).





- Solid understanding of containerization and orchestration (Docker, Kubernetes) for ML workloads.

- Experience with cloud infrastructure and infrastructure-as-code (Azure, Terraform, or similar).

- Solid cross-functional communication skills, partnering closely with data science and platform teams.

Good to Have

- Experience with model monitoring and observability tools (eg, Evidently, Prometheus, Grafana).

- Familiarity with feature stores and data versioning tools (eg, Feast, DVC).

- Exposure to LLM/GenAI model serving and fine-tuning pipelines.

- Relevant cloud or Kubernetes certifications (eg, Azure AI Engineer, CKA).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 MLOPS Professional (Hyderabad)
🏢 Nstarx India
📍 Hyderabad