What are the responsibilities and job description for the Software Engineering Manager, Engineering Productivity (EngProd) position at Google DeepMind?
Snapshot
We are looking for a Software Engineering Manager to lead our existing Engineering Productivity (EngProd) team. Are you passionate about amplifying the impact of world-leading AI researchers and engineers? Do you thrive on building high-performing teams and designing solutions that remove friction at scale? In this role, you will lead and grow a dedicated team focused on optimizing the tools, workflows, and infrastructure that underpin our groundbreaking research. You'll partner closely with research scientists and engineers, understand their complex needs, and drive the strategy for developing innovative, generalizable solutions. Your team will be instrumental in shaping how efficiently DeepMind operates and collaborates with key infrastructure teams across Google.
About Us
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
The Role
As the Engineering Manager for EngProd, you play a critical role in accelerating the pace of AI discovery at Google DeepMind. You are the bridge between the cutting-edge needs of our researchers and the vast capabilities of Google's engineering ecosystem. This isn't just about fixing bugs; it's about strategically identifying systemic bottlenecks and driving the design and implementation of high-leverage solutions.
You and your team will immerse yourselves in complex research projects to gain deep empathy for user pain points. You'll then translate these insights into a clear technical vision and roadmap for the EngProd team. The scope is broad – from optimizing build and test systems to improving large-scale compute orchestration and streamlining the entire ML development lifecycle. You'll champion a first-principles engineering mindset to tackle novel challenges and foster a culture of engineering excellence. This is a unique opportunity to influence AI development at its core, working across diverse technical domains and shaping the infrastructure that powers the future of AI.
Key responsibilities:
As the leader of the EngProd team, your primary responsibilities will be to:
You are a technically grounded leader passionate about creating force-multipliers for engineering and research teams. You have a strategic mindset, a knack for identifying systemic improvements, and a proven ability to lead teams to deliver impactful solutions.
Application deadline: 16th April 5pm BST
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
We are looking for a Software Engineering Manager to lead our existing Engineering Productivity (EngProd) team. Are you passionate about amplifying the impact of world-leading AI researchers and engineers? Do you thrive on building high-performing teams and designing solutions that remove friction at scale? In this role, you will lead and grow a dedicated team focused on optimizing the tools, workflows, and infrastructure that underpin our groundbreaking research. You'll partner closely with research scientists and engineers, understand their complex needs, and drive the strategy for developing innovative, generalizable solutions. Your team will be instrumental in shaping how efficiently DeepMind operates and collaborates with key infrastructure teams across Google.
About Us
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
The Role
As the Engineering Manager for EngProd, you play a critical role in accelerating the pace of AI discovery at Google DeepMind. You are the bridge between the cutting-edge needs of our researchers and the vast capabilities of Google's engineering ecosystem. This isn't just about fixing bugs; it's about strategically identifying systemic bottlenecks and driving the design and implementation of high-leverage solutions.
You and your team will immerse yourselves in complex research projects to gain deep empathy for user pain points. You'll then translate these insights into a clear technical vision and roadmap for the EngProd team. The scope is broad – from optimizing build and test systems to improving large-scale compute orchestration and streamlining the entire ML development lifecycle. You'll champion a first-principles engineering mindset to tackle novel challenges and foster a culture of engineering excellence. This is a unique opportunity to influence AI development at its core, working across diverse technical domains and shaping the infrastructure that powers the future of AI.
Key responsibilities:
As the leader of the EngProd team, your primary responsibilities will be to:
- Build, mentor, and coach a high-performing team of talented engineers, fostering a collaborative and inclusive team culture focused on impact.
- Develop and execute the technical and organizational strategy, aligning with broader research and engineering goals.
- Guide your team in designing, building, and maintaining robust, scalable, and user-friendly tools, systems, and workflows that significantly enhance researcher and engineer productivity.
- Deeply understand the challenges faced by researchers and engineers through direct engagement and data analysis. Translate these needs into prioritized team goals and impactful projects.
- Build strong relationships and collaborate effectively with AI researchers, other engineering teams within DeepMind, and key infrastructure partners across Google. Influence partner roadmaps to better serve DeepMind's needs.
- Oversee efforts to instrument, measure, streamline, and improve the systems core to DeepMind's development loop (e.g., code repositories, build/test systems, deployment pipelines, compute resource management).
- Effectively communicate your team's vision, progress, and impact to leadership and the wider organization.
You are a technically grounded leader passionate about creating force-multipliers for engineering and research teams. You have a strategic mindset, a knack for identifying systemic improvements, and a proven ability to lead teams to deliver impactful solutions.
- You lead by example: You foster engineering excellence and can guide technical discussions effectively.
- You are user-obsessed: You are driven to understand user pain points and build solutions that genuinely improve their experience and productivity.
- You think at scale: You have experience with, and enthusiasm for, leveraging large-scale distributed systems and tackling complexity.
- You are a strong communicator and influencer: You can articulate a vision, build consensus, and collaborate effectively across diverse teams and levels.
- You are passionate about developing people: You find joy in mentoring engineers and growing a successful team.
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- Past experience managing or technically leading small/medium software engineering teams.
- Strong understanding of the software development lifecycle, engineering best practices, and developer tooling.
- Excellent programming skills, particularly in Python and/or C , and experience with large codebases.
- Good understanding of modern AI/ML infrastructure, ideally including distributed systems, build/CI/CD systems, or large-scale compute environments.
- Excellent communication, interpersonal, and stakeholder management skills.
- An interest in Google DeepMind's mission and the advancement of AI.
- Experience specifically within an Engineering Productivity, Developer Tools, or SRE team.
- Deep familiarity with modern AI/ML infrastructure, workflows, and model lifecycle stages.
- Experience with large-scale distributed compute and workload scheduling systems (e.g., Kubernetes, Slurm, Borg).
- Experience with distributed build systems (e.g., Bazel).
- Experience designing and improving the User Experience (UX) of complex technical systems.
- Expertise in profiling, debugging, and optimizing complex systems (especially Python).
- Experience training or working with large-scale AI models.
- Contributions to maintaining and improving the health of large, complex code repositories.
Application deadline: 16th April 5pm BST
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
Manufacturing Engineering Manager
Endovascular Engineering -
Sunnyvale, CA
Manufacturing Engineering Manager
Endovascular Engineering -
Fremont, CA
Manufacturing Engineering Manager
Endovascular Engineering -
San Jose, CA
