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 processin... more details
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.
As a Software Engineers in Manufacturing Software Systems, you will analyze data and design, develop, test, deploy, maintain, and enhance software solutions. You will enable smart manufacturing which includes supply chain digitization, connected systems and proactive monitoring of insights. You will partner across platforms and devices to engineer efficient, accurate and secure software systems, streamline processes for teams such as Supplier Development Engineering, Technical Engineering, Product Quality, Reliability, Reverse Logistics, Factory Test, Design for Manufacturing and more.
Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.
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.
- Analyze data, recognize patterns and design solutions based on the observations.
- Write and review technical documents, including design, development, and revision documents.
- Identify and debug large systems using Google specific tools.
- Write, review and test code in compiled or scripted languages.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages (e.g., Java, C/C++, C#, Objective C, Python, JavaScript, or Go).
- 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning or natural language processing.
- Experience with designing algorithms for data analysis.
- Experience in implementing algorithms for data analysis and processing.
Preferred qualifications:
- Master's degree or PhD in Computer Science, or a related technical field.
- Experience in industrial or academic projects involving multiple people or teams.
- Experience with large-scale data processing and analysis, including data visualization to present analysis.
- Experience in building, tuning, and applying machine learning systems to solve real world problems.
- Ability to do research and execute the scientific process (e.g., experiment design and analysis).
- Ability to manage open-ended projects.