Posted:3 days ago|
Platform:
On-site
Full Time
We are looking for MLops Engineer@ Gurgaon Location
Job Responsibilities:
Design and implement CI/CD pipelines for machine learning workflows.
Develop and maintain production-grade ML pipelines using tools like MLflow, Kubeflow, or Airflow.
Automate model training, testing, deployment, and monitoring processes.
Collaborate with Data Scientists to operationalize ML models, ensuring scalability and performance.
Monitor deployed models for drift, degradation, and bias, and trigger retraining as needed.
Maintain and improve infrastructure for model versioning, artifact tracking, and reproducibility.
Integrate ML solutions with microservices/APIs using FastAPI or Flask.
Work on containerized environments using Docker and Kubernetes.
Implement logging, monitoring, and alerting for ML systems (e.g., Prometheus, Grafana).
Champion best practices in code quality, testing, and documentation.
Required Skills:
7+ years of experience in Python development and ML/AI-related engineering roles.
Strong experience in ML Ops tools like MLflow, Kubeflow, Airflow, or similar.
Deep understanding of Docker, Kubernetes, and container orchestration for ML workflows.
Hands-on experience with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code (Terraform/CDK).
Familiarity with model deployment and serving frameworks (e.g., Seldon, TorchServe, TensorFlow Serving).
Good understanding of DevOps practices and CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI).
Experience with data versioning tools (e.g., DVC) and model lifecycle management.
Exposure to monitoring tools for ML and infrastructure healt
Experience:7-12 Yrs
Job Location :Gurgaon
Interested candidates can share your CV to mangani.paramanandhan@bounteous.com, i will call you shortly. Please share your CV.
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