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Mid-level ML role in Bangalore with broad in-demand skills and 3–6 year range increases applicant competition.
Core ML, Python, MLOps, and AWS skills are broadly transferable across industries.
Explicit 3–6 years, mandatory ML, Python, CI/CD, AWS, and build-tool requirements raise strictness.
Design, develop, train, and deploy AI/ML models and end-to-end ML pipelines including data preprocessing, model training, validation, deployment, and monitoring.
Develop Python automation for test suites, model validation, workflow orchestration, and integrate ML pipelines into CI/CD workflows using tools like CMake and Bazel.
Deploy, monitor, and optimize ML workloads in AWS, collaborating with DevOps teams to implement MLOps practices such as model versioning and reproducibility.
3 to 6 years of hands-on experience in AI/Machine Learning development.
Strong proficiency in Python specifically for automation, ML model development, and testing.
Experience integrating ML workflows into CI/CD pipelines and using version control systems (Git, GitLab, GitHub).
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
Experienced in full ML model lifecycle management with practical knowledge of MLOps and cloud-based (AWS) deployments.
Skilled at building and maintaining stable ML build environments using CMake and Bazel with a strong DevOps and automation focus.
Capable of collaborating tightly with cross-functional and DevOps teams to deliver scalable, reliable AI solutions in an on-premise, office-based setting.