ML Ops Platform Engineer

Job Description

Job Role:

We are seeking a skilled MLOps Platform Engineer to build and maintain a robust platform for the entire Machine Learning (ML) lifecycle. This role involves automating ML model training, testing, deployment, and monitoring, integrating seamlessly with our existing infrastructure to accelerate ML innovation.

Key Responsibilities  

• CI/CD for ML: Develop and manage CI/CD pipelines for ML model code and infrastructure, covering unit, integration, and deployment to all environments.
• Automated ML Training: Design and implement pipelines for repeatable model training, automatic sweeps, data processing, and hyperparameter optimization.
• Include scheduling, queuing, and cost monitoring for training runs.
• Support training on cloud and on-premise GPU resources.
• Model Monitoring: Establish tools and dashboards for continuous monitoring of deployed ML models, ensuring health, availability, and performance.
• Platform Integration: Ensure the MLOps platform integrates with company workflows, data pipelines, and computing architecture.
• MLOps Best Practices: Promote and implement best practices for reproducibility, version control, and governance across the ML lifecycle.

Technical Skills 

• Strong experience MLOps, DevOps, or ML Engineering, focusing on ML infrastructure
• Programming: Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• CI/CD & Orchestration: Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions) and workflow orchestrators (e.g., Airflow).
• Model Serving & Deployment: Design and implement strategies for deploying ML models to production on Kubernetes, leveraging frameworks like BentoML or MLServer for efficient and scalable model serving.
• Cloud: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its ML services.
• MLOps Tools: Familiarity with MLOps platforms like Comet ML, MLflow, Kubeflow, SageMaker, or Vertex AI.
• Monitoring: Experience with ML model monitoring solutions.
• Experience with Infrastructure as Code (IaC) tools (e.g., Terraform).
• Knowledge of distributed training frameworks.
• Hands-On experience in Databricks & Data engineering. (PySpark is must or SQL/PostgreSQL/MySQL, NoSQL)

Job Description - Grade Specific

Has more than five year of relevant work experience. Solid understanding of programming concepts, software design and software development principles. Consistently works to direction with minimal supervision, producing accurate and reliable results. Individuals are expected to be able to work on a range of tasks and problems, demonstrating their ability to apply their skills and knowledge. Organises own time to deliver against tasks set by others with a mid term horizon. Works co-operatively with others to achieve team goals and has a direct and positive impact on project performance and make decisions based on their understanding of the situation, not just the rules.