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Genpact brand, Bengaluru metro location, and broad MLOps/CV skillset increase applicant competition.
Highly specialized CV and MLOps requirements make industry-background transferability limited.
Manager-level role with extensive mandatory MLOps and CV tooling implies moderate-to-strict technical screening.
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Own end-to-end automation of ML pipelines specifically for computer vision tasks including data ingestion, preprocessing, model training, evaluation, and inference.
Deploy and serve computer vision models in production environments using containerization (Docker) and orchestration platforms (Kubernetes), ensuring real-time and batch inference capabilities.
Implement monitoring and observability solutions to detect model drift, latency, and performance issues; optimize models for performance including edge deployment and support continuous integration with DevOps teams.
Hands-on experience with ML infrastructure, DevOps practices, and production-level computer vision pipelines.
Proficiency with tools such as MLflow, Kubeflow, DVC, Airflow, Docker, Kubernetes, and model-serving frameworks like TensorFlow Serving or Triton Inference Server.
Bachelor's or Master's degree in Business Administration, Communication, Marketing, or Sales (as explicitly mentioned).
Work Experience Required: Not explicitly mentioned in the JD.
Strong technical expertise in operationalizing and scaling computer vision ML models across cloud and edge environments.
Experience collaborating closely with data scientists and DevOps teams to integrate models into CI/CD pipelines and ensure production readiness.
Familiar with pipeline automation, model optimization techniques (quantization, pruning), and monitoring frameworks (Prometheus, Grafana).