Software Engineer AI/ML, Devices and Services

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning or natural language processing

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 3 years of experience with software development in one or more programming languages, and with data structures/algorithms.
• 3 years of experience testing, maintaining or launching software products, 1 year of experience with software design and architecture.
• 3 years of experience with AI/ML algorithms and tools (e.g., TensorFlow), deep learning, or natural language processing or other Machine Learning.
• Experience designing and developing solutions for a business such as supply chain, sales, finance.
• Experience in multiple full system implementation life cycles (analyze, design, build, test, implement, support)

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 Devices and Services Systems team designs, builds, and maintains the software systems backbone that enables the manufacturing, product design, sourcing, planning, fulfillment and execution, and sales serving for all consumer devices designed and sold by Google including Pixel, Fitbit, and Nest. Our systems support orders from both retailers and end customers and help optimize the on-hand, in-transit, and planned supply against orders and projected demand. We are actively applying AI/ML technologies across our solutions to enhance these processes. We manage a global inventory and lifecycle of all devices made/sold, providing comprehensive fulfillment and execution, return, repair, and replacement options to our user base and partners. Our solutions assist operations teams in planning and sourcing device components as well as manufacturing.

The US base salary range for this full-time position is $136,000-$200,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

Responsibilities

• Develop and deploy systems and services that improve supply chain and financial processes working with industry-leading analysts for design
• Build solutions with custom frontend and backend services while maintaining highest levels of development practices including: technical design, solution development, test execution and automation, issue identification and resolution, and writing clean, modular and self-sustaining code.
• Develop and redesign Machine Learning (ML) models and data pipelines to enable ML productionization for Google first party products and services
• Guide team members. Present findings to team members and help set a direction for future Machine Learning (ML) experiments and productionization
• Communicate and collaborate with cross-functional teams like Technical Program Managers (TPgMs), Data Engineers, Data Scientist, Business Systems Analyst and Operations, while also triaging system or service issues and debug/track/resolve by analyzing the issues and the impact on business processes