Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 1 year of experience with data structures or algorithms.
• 1 year of experience building and developing infrastructure or distributed systems.

Preferred qualifications:

• Experience with machine learning theory and algorithms.
• Experience with back-end development in C++ or Python.
• Background in data science/analytics.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google's artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.

Responsibilities

• Develop large-scale data ingestion and processing pipelines.
• Build systems to fine-tune, evaluate, and visualize the performance of ML systems.
• Work on releasing face authentication model drops for in-market and unreleased Pixel devices.
• Expand existing authentication infrastructure stack to support other devices and ML teams.