- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Seattle, WA, USA; Goleta, CA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development, with a focus on distributed computing.
- 3 years of experience in a technical leadership role, guiding engineers to design and implement client-side tools or APIs.
- 2 years of experience in a people management or team leadership role.
- Experience with client-side development, including the architecture of client libraries, command line interface (CLI) tools, or web interfaces.
Preferred qualifications:
- Experience with Google Cloud Platform technologies, such as Compute Engine or Cloud Spanner.
- Experience with Kubernetes and Google Distributed Cloud.
- Experience designing gRPC APIs.
- Experience designing and maintaining client interfaces - web UIs, libraries and CLIs.
- Familiarity in quantum computing.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Google’s Quantum AI team builds and runs algorithms on today’s leading quantum computers. As these machines grow from research prototypes into products, the software that orchestrates and executes quantum computations will need to transition into a form that more closely resembles traditional software products.
This role focuses on customer tools for Quantum AI hardware systems. The technical scope spans APIs, UIs, CLIs and client libraries for managing quantum processors and user workloads run on them. This role works closely with the research, product, and software teams on the Quantum AI team. Much of this work is greenfield, representing an opportunity for high impact.
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Scope problems and recommend solutions for both short and long-term needs, taking ownership of goal and roadmapping to influence other engineers, and implementing solutions or delegating to colleagues.
- Drive outcomes as a key contributor, designing or implementing projects that span multiple quarters without supervision, and consistently generating the ideas required to solve ambiguous problems.
- Write and review code to ensure best practices are met, contributing to data preparation, optimization, and performance enhancements confirming all aspects of technical work are high quality.
- Seek out and incorporate feedback on designs to determine when to enhance existing systems or build new systems, and contribute to existing documentation or educational content.
- Work closely with other research groups and collaborate with teams of different backgrounds, including hardware engineers, electronic engineers, or research scientists.