Found Description
Responsibilities
- Technical Delivery (60%): Design and implement end-to-end ML solutions from experimentation to production; Build scalable ML pipelines and infrastructure; Optimize model performance, efficiency, and reliability; Write clean, maintainable, production-quality code; Conduct rigorous experimentation and model evaluation; Troubleshoot and resolve complex technical challenges.
- Collaboration and Contribution (25%): Mentor junior and mid-level ML engineers; Conduct code reviews and provide constructive feedback; Share knowledge through documentation, presentations, and workshops; Collaborate with cross-functional teams (DevOps, Data Engineering, SAs); Contribute to internal ML practice development.
- Innovation and Growth (15%): Stay current with ML research and emerging technologies; Propose improvements to existing solutions and processes; Contribute to the development of reusable ML accelerators; Participate in technical discussions and a...