Software Engineer III, Research Infrastructure
Job Summary
Job Description
- GenAI solution implementation
- ML infrastructure expertise
- Data optimization and processing
- API and data pipeline development
- Collaboration with research teams
- Experience with accessible technologies
- Health/fitness or wearables tech experience
- User experience design knowledge
- Data privacy and security understanding
- Master's/PhD in Computer Science
- Bonus
- Equity
- Benefits
9 skills required
Job Details
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.
- 2 years of experience with data structures or algorithms.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 1 year of experience with core GenAI concepts (large language models, multi-modal, large vision models), and experience with text, image, video, or audio generation.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing accessible technologies.
- Experience in health and fitness or wearables technologies.
- Experience in user experience concerns, surveys, iterative design, research, and mocks, with a good understanding of data privacy and security concerns.
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.
Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.
Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.
The US base salary range for this full-time position is $141,000-$202,000 + 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 .
Responsibilities
- Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.
- Design infrastructure for scalable usage of collected research data, adding functionality and features needed by research teams and integrating with upstream data sources.
- Build data interfaces and APIs to standardize incoming data for rapid research iteration and evals for the PHA and wearable studies. Investigate new ML and GenAI tools for infrastructure support, designing necessary APIs or standard processing.
- Ensure efficient and reliable data pipelines, addressing optimization and debugging. Ensure robust API and standard data processing documentation for research and algo team self-service.
- Collaborate with research and algo teams within Google, ensuring quick access to high-quality data from wearables, mobile apps, and algos. Audit research and development engineers need in ML and GenAI to provide standardized infrastructure.
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About The Company
A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.
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