Software Engineer, Machine Learning, Pixel Watch

Minimum qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with machine learning algorithms and tools, or applied ML

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, and/or cross-business projects.
• Experience using digital signal processing techniques, working with sensor data (e.g. accelerometer data), and writing and deploying features in C++.
• Experience optimizing and launching machine learning (ML) based features on consumer electronics products.
• Experience with real-time operating systems (e.g. Android).

As a Staff Software Engineer, you will develop on-device machine learning algorithms for our next generation Pixel Watches. You will work with Product, UXD, UXR, Quality Assurance, and other engineering teams to ideate, create, and deliver high quality ML based experiences for our users. In addition to your direct contributions, you will serve as the technical lead for algorithm development efforts on the team, consulting and providing mentorship to other algorithm developers.

• Develop user-facing features powered by ML algorithms. Experiment, fine tune, and deploy features that run on-device in low power, memory constrained environments.
• Work with UXR teams to define and collect user data, build and train ML models using various techniques, and evaluate their performance. Refine and iterate models based on feedback from product managers, user studies and feedback, and production.
• Optimize for the device and user. Understand the tradeoffs between algorithm accuracy, power, compute, memory, and latency, and make optimization decisions based on an understanding of the big picture.
• Serve as technical lead for algorithm development on the team. Guide and mentor other developers, and stay up to date with the latest advancements in machine learning techniques and tools and help grow the team's expertise. Develop a technical roadmap of new features and feature improvements.