MLOps Developer (MResult)

Key Responsibilities

• Handle end-to-end deployment activities for ML models.
• Automate the build, training, and deployment processes of machine learning models.
• Develop automation for training of various ML methods.
• Troubleshoot deployment and pipeline-related issues.
• Govern and monitor deployed ML models, ensuring compliance and performance.
• Manage and support software dependencies and environment consistency.

What We're Looking For

• Hands-on experience with MLOps tools and frameworks.
• Practical knowledge of ML platforms like Amazon SageMaker, Azure ML, or open-source MLOps tools.
• Proficiency in Python for scripting and automation.
• Experience working with Agile methodologies and CI/CD workflows.
• Exposure to cloud platforms — preferably AWS or Azure.
• Familiarity with Docker and Kubernetes (added advantage).
• Strong communication and collaboration skills.