ML Engineering Manager
- Lead the Amazon Customer Interests team (in Amazon Core Personalization org) to build and enable experiences that inspire customers to explore their interests by enabling... more discovery of content related to these interests
- Developed team's structure, vision, software and strategy generating over $75M
- Managed team performance and represent my team at leadership reviews related to team's yearly roadmaps, business metrics, and performance ratings
- Recruited 10+ software engineers and applied scientists within 2 weeks using my LinkedIn network, via a pipeline of 100+ candidates
- Spearheaded the initiation of Scrum-of-Scrums, risk management, & developer training in addition to proposing & implementing the use of Gantt charts resulting in an overall 40% reduction in workflow friction
- Designed & built applications to personalize the notifications and hints sent to headless and headed Alexa devices (50 million+)
- Created techniques (Amazon filed a patent) for improving accuracy of reinforcement learning experiments on Amazon product pages that reduced the number of failed experiments by 40% and saved 60% in redundant manual effort
- Developed, standardized, & delivered training maximizing error analysis tools effectiveness reducing error escalations by 38%.
- Conducted interviews (150+) and evaluated work artifacts for promotion of software engineers to senior software engineers
- Developed team's structure, vision, software and strategy generating over $75M
- Managed team performance and represent my team at leadership reviews related to team's yearly roadmaps, business metrics, and performance ratings
- Recruited 10+ software engineers and applied scientists within 2 weeks using my LinkedIn network, via a pipeline of 100+ candidates
- Spearheaded the initiation of Scrum-of-Scrums, risk management, & developer training in addition to proposing & implementing the use of Gantt charts resulting in an overall 40% reduction in workflow friction
- Designed & built applications to personalize the notifications and hints sent to headless and headed Alexa devices (50 million+)
- Created techniques (Amazon filed a patent) for improving accuracy of reinforcement learning experiments on Amazon product pages that reduced the number of failed experiments by 40% and saved 60% in redundant manual effort
- Developed, standardized, & delivered training maximizing error analysis tools effectiveness reducing error escalations by 38%.
- Conducted interviews (150+) and evaluated work artifacts for promotion of software engineers to senior software engineers
