Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
• Experience with embedded systems/firmware design.
• Experience in Distributed Computing and Parallel Computing.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.
• Experience in software development for optimization power/performance.

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.

Responsibilities

• Design, implement, and maintain robust on-device and offline recording and playback technologies for multimodal sensor and perception data.
• Optimize and sandbox video and audio processing codecs to guarantee system stability, compliance, and performance under complex security constraints.
• Maintain and scale the dataset decode infrastructure used directly by hardware calibration and testing teams in production environments.
• Build high-performance exporter tools and APIs to demux, extract, and format time-synced sensor metadata and device profiles.
• Support automated test automation and hardware simulation platforms through high-throughput stream playback engines.