Minimum qualifications:- Bachelor's degree in Computer Science, or a related technical field or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages (e.g., Python, C, C , Java, JavaScript).
- Experience in Quality Assurance (QA) or Quality Engineering (QE), Development and Operations (DevOps), engineering productivity, Continuous Integration/Continuous Deployment (CI/CD) and product quality.
Preferred qualifications:- Experience partnering with or working within an Engineering Productivity (EngProd) or Developer Experience organization to improve engineering workflows.
About the jobThis is a dedicated Software Quality and Engineering Productivity individual contributor role. We are looking for a software engineer passionate about software quality, automated testing, release discipline, and engineering productivity, with a strong emphasis and experience with large-scale data storage and processing systems. As robotics data is expected to grow 10-50x over the upcoming years, we need dedicated talent to help us build, maintain, and optimize our testing and quality ecosystem in this particular area.
Robotics infrastructure is uniquely difficult. You will help solve problems at the intersection of large and rapidly growing raw data storage and flexible data processing to support complex model training. Your work will directly impact our systems quality and engineering velocity, determining how efficiently our engineers and scientists can run iterations with new data and test new models.
We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Develop and Maintain Testing Infrastructure, implement and support software testing systems focused on data storage and processing for large scale and rapidly growing robotics data.
- Build and manage robust CI/CD pipelines and stage environments for data processing systems. Implement comprehensive regression checks that protect both correctness and performance at scale.
- Enhance engineering productivity, monitor engineering productivity metrics and build tooling to eliminate bottlenecks and reduce productivity drag. Help maintain code health and productivity as our data processing systems evolve rapidly.
- Collaborate with senior engineers to identify and apply advanced automation and AI tooling within our data ecosystem.
