Role : You'll 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.ref : hirist.tech)