About this role
Develop production-ready applications and systems using AI tools and cloud AI services, with a focus on operationalizing machine learning models. The role may also apply generative AI models, deep learning, neural networks, chatbots and image processing.
Responsibilities
- Design, build and maintain scalable model-training pipelines. Deploy secure, low-latency model services for marketing applications using Docker, FastAPI and AWS; manage batch and real-time inference.
- Automate testing, model validation and deployment through CI/CD workflows, including GitHub Actions. Manage model versioning, packaging, registration and reproducibility across the ML lifecycle.
- Monitor production model performance, data drift and system health; establish alerts and dashboards, and initiate retraining or tuning when needed.
- Improve processes, collaborate on decisions across teams, solve team and cross-team problems, share knowledge and monitor progress against strategic goals.
Requirements
At least 7.5 years of experience is required, including a stated minimum of 7.5 years in Machine Learning Operations; the listing also labels the role as 5–10 years of experience. Proficiency in MLOps, cloud AI services and deployment strategies, multi-cloud skills, experience with machine learning frameworks, and the ability to optimize models for production are required. Experience with MLflow and Airflow is mandatory. The posting requires 15 years of full-time education.
Location: The job header lists Indore, while the description says the position is based at the Bengaluru office.