About the position
Amazon is seeking a talented Software Development Engineer II to join our AI Technology team within Amazon's Consumer Electronics Technology (CE-Tech) organization. You'll be part of a team that drives AI innovation across Amazon's BEATS division, working on modern applications of machine learning and generative AI to enhance customer shopping experiences and vendor/internal tooling. The ideal candidate is passionate about new opportunities and has a demonstrable track record of success delivering new features and products and a demonstrated interest in AI/ML technologies. The right candidate will have exceptional technical expertise and have thrived and succeeded in delivering high quality technology products/services in an agile environment. They’re also comfortable working with an ambiguous problem, trying many things, breaking few things, learning a lot, and doing it better the next round. If that sounds like you, then a commitment to team work, hustle, and strong communication skills (to both business and technical partners) will make you a perfect fit for our team.
Responsibilities
- Design, develop, and maintain innovative and scalable ML systems and AI-powered features that serve millions of customers as well as partners and internal users
- Evaluate AI technologies and architectures when developing solutions, and specify/implement improvements like fine-tuning or training custom ML models
- Collaborate with Applied Scientists to implement and optimize ML models and algorithms
- Write high-quality, maintainable code with comprehensive test coverage and documentation
- Participate in architecture discussions and contribute to technical design decisions
- Mentor junior engineers and provide technical guidance in code reviews, keeping the bar high for maintainable and extensible code
- Collaborate with product, applied science and other key stakeholders to define technical requirements and delivery timelines. Integrate feedback to enhance design and establish feedback loops for continuous improvement based on user metrics
- Build and maintain monitoring systems for ML applications in production
- Contribute to the team's technical strategy and apply best practices for code building and customer scaling requirements
