5 - 10 years
20 - 35 Lacs
Posted:4 weeks ago|
Platform:
Hybrid
Full Time
Youll need to work closely with Data Scientists, Data Engineers, UI Engineers, Software Developers, and DevOps teams to design and implement end-to-end AI/GenAI solutions. You will: Be responsible for training, integrating, and deploying AI/GenAI/ML models in Azure/AWS ecosystem. Design and implement enterprise-quality AI/GenAI/ML applications. Optimize deployed models for performance, scalability, and efficiency. Debug and troubleshoot issues in AI/GenAI/ML pipelines and systems. Monitor model performance in production and retrain as necessary to maintain accuracy. Stay conversant with the latest trends, techniques, and tools in GenAI pipelines. Experiment with state-of-the-art methods and propose innovative solutions to complex problems. Excellent written and verbal communication skills required. Technical Skills: Excellent Python, PySpark, and SQL skills. Knowledge of GenAI stack is a big plus. Experience with Azure DevOps / AWS DevOps for ML projects, Databricks, CI/CD pipelines, and repositories. Experience with Azure/AWS MLOps/Kubeflow. Experience of training and deploying AI/GenAI/ML models into production environments and integrating them with existing systems. Knowledge of containerization tools like Docker, orchestration systems like Kubernetes, and inference platforms like Kserve / NVIDIA Triton. Knowledge of Azure / AWS ETL pipelines is a plus (but not mandatory). Soft Skills: Excellent written and verbal communication. Exceptional problem-solving and multitasking skills in a fast-paced environment. Experience Level: 8+ years of experience in ML Engineering.
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