Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessSpecialized MLOps skillset, mid-level experience, and moderate employer brand lead to medium competition.
Highly specialized MLOps tooling and GPU operations make background fit highly sensitive.
Explicit 3-5 years plus mandatory Docker, Kubernetes, Triton, GPU and cloud skills enforce high shortlisting strictness.
Job Description
Structured overview of role & requirementsAbout 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.