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Job Description
Structured overview of role & requirementsAbout This Role
Develop, train, and evaluate machine learning models in collaboration with data scientists.
Build, maintain, and automate MLOps pipelines covering data ingestion, feature engineering, model training, deployment, and monitoring on cloud platforms (AWS, GCP, Azure).
Implement monitoring systems and conduct A/B testing to optimize model performance and ensure reliability.
Minimum Requirements
Master’s degree with 5+ years experience or Bachelor’s degree with 7-9+ years experience in Computer Science, IT, or related field.
Proficiency in machine learning algorithms and MLOps tools (e.g., MLflow, Kubeflow, Airflow).
Experience with DevOps tools (Docker, Kubernetes, CI/CD) and cloud platforms (AWS, GCP, Azure).
Strong programming skills in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn).
Ideal Candidate Profile
Experienced in operationalizing machine learning models end-to-end including production deployment and monitoring.
Comfortable working in a cloud environment and implementing automated ML workflows using DevOps/MLOps best practices.
Skilled in collaborating across data science, engineering, and product teams to deliver scalable ML solutions.