Google Foundation Jobs in California (NOW HIRING)

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience with software development in one or more programming languages (e.g., Python, C, C , Java, JavaScript).
• 5 years of experience with design and architecture; and testing/launching software products.

Preferred qualifications:

• Master's degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience in a technical leadership role across a large organization.
• Experience bringing a new product or significant feature-set to market.
• Experience with streaming media, ideally live-streamed video at scale
• Experience with building or building on top of AI foundation models.
• Strong stakeholder management, alignment, and cross-company partnership skills, with experience developing joint product and engineering roadmaps cross-functionally.

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.
As the Engineering Lead, you will serve as the chief technical authority managing the architecture, and cross-company integration of a new AI-native product, leading it through the full 0-to-1 life-cycle. You will move from idea explorations to prototyping, cross-company collaboration and experimentation. You will embrace ambiguity to refine concepts into lovable products. You will translate complex multi-modal technologies into robust software, support a core team, and mentor staff leads. Partnering with research and product teams you will deliver a seamless, low-latency engine for novel applications. You are an expert systems architect with a background in ML and real-time media, spatial, or XR systems.
Labs is a group focused on incubating early-stage efforts in support of Google's mission to organize the world's information and make it universally accessible and useful. Our team exists to help discover and create new ways to advance our core products through exploration and the application of new technologies. We work to build new solutions that have the potential to transform how users interact with Google. Our goal is to drive innovation by developing new Google products and capabilities that deliver significant impact over longer timeframes.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $262000 - $364000 (USD) 25% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities

• Set and communicate team priorities that support the organization's goals. Align strategy, processes, and decision-making across teams.
• Set expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
• Develop the long-term technical goal and roadmap within, and often beyond, the scope of your teams. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
• Oversee systems designs within the scope of the area, and review product or system development code to solve ambiguous issues.
• Drive technical project strategy, lead ML infrastructure optimization, and oversee the design and implementation of solutions across multiple specialized ML areas.

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