DevOps+MLOps+PythonML

Job Description:

• About the job
• Build automate and scale intelligent systems that move seamlessly from experimentation to reliable production
• In this role you ll work at the intersection of DevOps and MLOps helping teams ship ML powered features faster safer and with measurable impact
• You ll partner closely with data scientists engineers and platform teams to create repeatable pipelines production grade deployments and strong observability across environments
• If you enjoy solving real world reliability challenges improving developer experience through automation and enabling ML models to perform consistently in production this is a great opportunity to grow your ownership and technical depth while contributing to a collaborative high learning culture

Key Responsibilities:

• Key Responsibilities
• Platform Automation
• Design and maintain CI CD workflows to automate build test release and deployment processes for ML and supporting services
• Implement infrastructure automation and configuration management to ensure consistent environments across dev staging and production
• Improve system reliability through monitoring alerting incident response practices and post incident improvements
• MLOps Model Delivery
• Build and manage ML pipelines for training validation packaging and deployment with reproducibility and traceability
• Enable model versioning artifact management and controlled rollouts e
• g
• canary blue green for ML services
• Establish model performance monitoring drift detection signals and feedback loops for continuous improvement
• Collaboration Engineering Excellence
• Work with data science teams to productionize Python ML code with robust testing packaging and runtime optimization
• Define operational standards logging metrics SLOs and contribute to documentation and runbooks
• Participate in code reviews and propose improvements to security scalability and cost efficiency
• Minimum Qualifications
• BTECH MTECH MCA MSC or equivalent practical experience
• 2 3 years of hands on experience in DevOps and or MLOps focused engineering roles
• Working experience with CI CD concepts and automation for deployments and releases
• Practical experience supporting Python based ML workloads packaging environments dependency management runtime troubleshooting
• Strong understanding of Linux fundamentals networking basics and system troubleshooting

Technical Requirements:

• SKILLS
• DevOps MLOps PythonML
• Good to have skills
• Docker Kubernetes Terraform MLflow Airflow

Additional Responsibilities:

• Preferred Qualifications
• Experience productionizing ML workflows end to end training pipelines model registry artifacts deployment monitoring
• Exposure to containerization and orchestration for scalable ML services e
• g
• Docker Kubernetes
• Familiarity with Infrastructure as Code and configuration tools e
• g
• Terraform Ansible
• Experience with ML lifecycle tooling e
• g
• MLflow Kubeflow and workflow orchestration e
• g
• Airflow
• Hands on exposure to LLM enabled applications including deployment patterns inference optimization and evaluation monitoring approaches
• Strong communication skills to align platform practices across engineering and data science stakeholders

Preferred Skills:

Technology->Devops->Ansible,Technology->AI-AI Engineering->MLOps,Technology->OpenSystem->Python - OpenSystem,Technology->AI-Data science->Machine Learning