Machine Learning Engineer — MLOps
Indexed description
Machine Learning Engineer — MLOps
Build and maintain ML pipelines, CI/CD for models, and observability to ensure models are reproducible, monitored and safely serving predictions in production.
Tasks
- Design end-to-end MLOps pipelines: data ingestion, training, validation and deployment.
- Implement model CI/CD, automated testing, and canary/rollback strategies.
- Build monitoring for model performance, data drift and alerts.
- Work with infra teams to optimize cost, scaling and reproducibility of model workloads.
- 3+ years in ML engineering or SRE with experience building MLOps pipelines.
- Experience with orchestration (Airflow, Kubeflow), infra-as-code and CI systems.
- Familiarity with model serving frameworks (TorchServe, TF Serving, Triton) and monitoring tools.
- Strong Python skills and experience with cloud platforms (AWS/GCP/Azure).
Cloud & GPU credits
Professional development and certification support
Flexible working and hybrid options
Job details
Job type
Full-time
Location
Remote / In-house (Hybrid)
Salary
₹110k – ₹180k INR (depending on experience)
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