Infosys - Computer Vision MLOps Engineer in Bangalore, भारत

We are seeking an experienced Computer Vision MLOps Engineer to design, build, deploy, and manage production-grade computer vision and machine learning https://jobeax.com/link/1Rn7zv9wYEsoo7Eu role combines strong expertise in computer vision, machine learning engineering, cloud infrastructure, and MLOps practices to enable reliable and scalable deployment of vision-based AI https://jobeax.com/link/5WM6jVJPxXxkaX5M ideal candidate will have experience taking computer vision models from development and experimentation through production deployment, monitoring, optimization, and continuous https://jobeax.com/link/DPiysjYX1KLnjeds Responsibilities :- Design and develop scalable MLOps pipelines for computer vision and machine learning applications.- Build and productionize computer vision models for image classification, object detection, image segmentation, OCR, tracking, and related use cases.- Develop end-to-end workflows covering data preparation, model training, validation, deployment, monitoring, and retraining.- Implement automated CI/CD pipelines for machine learning and computer vision model deployment.- Containerize ML applications and models using Docker and deploy them across cloud or containerized environments.- Design and manage model serving infrastructure for low-latency and high-throughput inference.- Implement model versioning, experiment tracking, artifact management, and reproducible ML workflows.- Build automated data and model pipelines to support continuous training and deployment.- Establish monitoring mechanisms for model performance, data quality, latency, resource utilization, and production drift.- Optimize computer vision inference pipelines for performance, scalability, and cost efficiency.- Work on model optimization techniques such as quantization, pruning, batching, and hardware acceleration where required.- Deploy and manage ML workloads across cloud platforms and Kubernetes-based environments.- Collaborate with data scientists and computer vision engineers to convert experimental models into production-ready solutions.- Develop APIs and services for integrating computer vision models with enterprise applications.- Implement appropriate logging, alerting, observability, and failure-recovery mechanisms for production ML systems.- Support troubleshooting of model, infrastructure, deployment, and inference-related production issues.- Establish best practices around ML lifecycle management, governance, security, and deployment standards.- Evaluate new MLOps tools, frameworks, and technologies to improve the overall ML development and deployment ecosystem.- Mentor junior engineers and contribute to technical architecture and engineering https://jobeax.com/link/NKlt3YnZFxTxA2qx Skills :- 10 - 12 years of experience in Machine Learning, Computer Vision, MLOps, or related engineering roles.- Strong hands-on experience with computer vision and deep learning applications.- Experience with frameworks such as PyTorch, TensorFlow, OpenCV, or equivalent technologies.- Strong programming skills in Python and experience developing production-grade ML applications.- Hands-on experience building and managing end-to-end MLOps pipelines.- Strong knowledge of ML lifecycle management, model deployment, model versioning, and monitoring.- Experience with Docker, Kubernetes, and containerized ML workloads.- Experience with CI/CD tools and automation for ML model deployment.- Strong understanding of cloud platforms such as AWS, Azure, or GCP.- Experience with ML orchestration and pipeline tools such as Kubeflow, MLflow, Airflow, or equivalent.- Experience with REST APIs, microservices, and production model-serving architectures.- Strong understanding of Git, Linux, automated testing, and deployment practices.- Experience with model optimization and inference performance tuning.- Good understanding of data pipelines, feature/data validation, model drift, and monitoring.- Strong debugging and problem-solving capabilities.- Experience designing scalable and highly available AI/ML platforms.- Good communication skills with the ability to work across data science, engineering, product, and business teams (ref:hirist.tech)