Senior Software Engineer, Manufacturing Software Systems

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 5 years of experience with software development in one or more programming languages.

Preferred qualifications:

• 5 years of experience with data structures/algorithms.
• 2 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning or natural language processing.
• Ability in implementing algorithms for data analysis and processing.
• Excellent investigative skills in designing algorithms for data analysis.

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 Manufacturing Software Systems team partners across Platforms and Devices to engineer efficient, accurate and secure software systems to streamline processes for teams such as Supplier Development Engineering, Tech Engineer, Product Quality, Reliability, Reverse Logistics, Factory Test, Design for Manufacturing and more.

In this role, you will work on projects utilizing AI agents or general software tools to automate processes and leveraging machine learning (ML) to analyze manufacturing data and identify opportunities to optimize process parameters, reduce waste, and improve overall efficiency. You will design, build, and maintain scalable ML infrastructure to support the development, deployment, and monitoring of ML models in a manufacturing environment. You will create and optimize data pipelines to ingest, process, and transform large volumes of manufacturing data from various sources.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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

• Analyze data, recognize patterns and design solutions based on the observations. 
• Write and review technical documents, including design, development, and revision documents.
• Write, review and test code in compiled or scripted languages.
• Identify and debug large-systems using Google-specific tools.