Responsibilities:
- Play a critical role in setting the MLOPs platform direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence.
- Be a go-to person to escalate the most complex online/production performance and evaluation issues, that require an in-depth knowledge of how the machine learning system and its components interact with systems around it.
- Develop and deploy AI models using machine learning techniques such as deep learning, neural networks, and chatbots.
- Apply GenAI models as part of the solution and ensure proper cloud or on-prem application pipeline with production-ready quality.
- Suggest, collect and synthesize requirements and create effective feature roadmap.
- Ability to visualize, articulate and develop an MLops framework and be aware of trade-offs of multiple approaches.
- Understand the on-going work and priorities within the team and help plan for the upcoming tasks within the sprint and beyond.
- Partner with the product team to understand the problem space, the competitive landscape and constraints and help deliver engineering solutions that work both for the customer and IBM.
- Lead design/code reviews, provide direction, implement features with high quality secure code, improve test coverage, performance and observability.
- Mentor junior team members.
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