Staff Software Engineering Manager, Sustainability and Efficiency

1 Hour ago • 8-11 Years • Artificial Intelligence • DevOps • Backend Development • $197,000 PA - $291,000 PA

Job Summary

Job Description

This Staff Software Engineering Manager role at Google focuses on carbon reduction optimizations for compute infrastructure. You'll lead a team in developing analytics, models, tools, and systems to evaluate and implement solutions for both general purpose compute and accelerated Machine Learning platforms. Responsibilities include setting team priorities, aligning strategies across teams, providing performance feedback and coaching to individuals, developing technical roadmaps, modeling workloads to drive architecture design, and analyzing energy efficiency to mitigate emissions. The role involves managing engineers across multiple teams and locations, overseeing large-scale projects internationally, and contributing to product strategy.
Must have:
  • 8+ years software development experience (Python, C++, Java, JavaScript etc.)
  • 3+ years technical leadership, 2+ years people management
  • Experience in Performance, System Architecture, Data Analysis
  • Set team priorities, provide performance feedback
  • Develop technical roadmaps, model workloads
  • Analyze energy efficiency, mitigate emissions
Good to have:
  • Master's/PhD in CS
  • Experience with multiplex organizations
  • Computer architecture, energy/performance modeling
  • Large-scale distributed systems, ML, networking, databases
  • Emissions accounting, reporting, auditing

Job Details


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).
  • 3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.
  • Experience in Performance, System Architecture, and Data Analysis.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • 3 years of experience working in a multiplex organization.
  • Experience with computer architecture, energy analysis/modeling, performance analysis/modeling.
  • Experience with large-scale distributed systems, ML, networking, databases, queuing theory, and related software infrastructure.
  • Experience in emissions accounting, reporting, auditing and standards interpretations.

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.

To meet Google's increasing Large Language Model (LLM) and Cloud demands while accelerating zero carbon, we need to identify and implement novel solutions to flatten the life-cycle carbon emission curves for our compute infrastructure, which requires a new suite of analytics, models, tools, and systems for exploring and evaluating effective ideas.

In this role, you will be working on carbon reduction optimizations for both general purpose compute and accelerated Machine Learning (ML) platforms, with an emphasis on hardware-software co-optimizations for both Cloud and internal use cases.

The ML, Systems, and Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary range for this full-time position is $197,000-$291,000 + 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

  • Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
  • Set clear 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 mid-term technical goal and roadmap within the scope of our often multiple teams. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
  • Ensure the team effectively models and analyzes key Google and Cloud workloads to drive server platform architecture design.
  • Direct efforts in carbon life-cycle and energy efficiency analysis for deployed platforms to understand and mitigate emissions from Google's compute infrastructure.

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