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We are seeking an experienced Software Engineering Manager to lead a team of engineers and researchers focused on optimising performance of AI / ML models across Alphabet. You will play a crucial role in accelerating research breakthroughs, streamlining the research-to-production pipeline, and ultimately accelerating the delivery of cutting-edge AI deployments. This role requires expertise in developing and leading experts in system performance and familiarity with working across the stack, from programming frameworks to compilers. Equally important is a passion for building and leading well-functioning teams: as the team's engineering lead, you will play a vital role in maximising the team's overall impact!

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.

As an Engineering Manager in the ML Performance space, you will lead a team of talented software engineers in tackling the complex challenges of optimising AI models at scale. This includes improving the efficiency of training and inference workloads and optimising performance of the latest models on Google’s fleet of hardware accelerators - throughout the entire model lifecycle.

This role is crucial for accelerating the delivery of cutting-edge AI! You will have the opportunity to shape the future of AI at Alphabet by driving innovation in research deployment, ultimately impacting users at the Alphabet scale across a diverse range of applications.

• Lead and manage a team of engineers: Foster a collaborative and impactful environment, providing mentorship and guidance to team members. Actively invest in their professional development through regular feedback, coaching, and opportunities for growth.
• Work closely with Technical Leads and Managers: Collaborate on technical direction setting and ensure alignment with overall deployment strategy. Provide guidance based on your domain knowledge and experience.
• Drive technical excellence for ML performance: Oversee the implementation of strategies for optimising performance across our workloads. Leverage your domain expertise to guide technical decisions and ensure best practices are followed.
• Collaborate with key stakeholders: Partner with research teams, infrastructure teams, and product teams to ensure seamless integration and alignment with broader research and development goals.
• Track and measure progress: Define and monitor key performance metrics to assess the effectiveness of ML performance optimisation strategies and identify areas for improvement.
• Champion a culture of collaboration and innovation: Encourage experimentation and creative problem-solving within the team.
• Stay abreast of industry trends: Continuously evaluate emerging technologies to maintain a competitive edge.

You will have a chance to make a significant impact on the Google DeepMind mission by identifying, and building ground-breaking solutions for fundamental engineering challenges. You will provide team and thought leadership, influencing our long-term engineering direction and contributing through a range of high impact initiatives in a critical strategic space for Alphabet.

The role will suit candidates who enjoy working with state-of-the-art AI in a fast-moving and dynamic space, and have a passion for collaborative problem domains. You should exhibit exceptional creativity when approaching difficult or ambiguous problems, distilling big-picture challenges into tractable projects for your engineers and elevating others to succeed.

In order to set you up for success as a Software Engineering Manager at Google DeepMind, we look for the following skills and experience:

• A degree in computer science, AI or equivalent experience.
• Experience of managing small to mid-sized teams (between 5 and 10 contributors) and comfort in managing other people managers.
• Experience in working on machine learning infrastructure or high performance computing infrastructure.
• Experience working with researchers and engineers working in research domains.
• Experience and comfort working in and leading within a highly collaborative and interdisciplinary environment.
• Experience leading a team that collaborates across time zones, primarily between California and the U.K.

In addition, the following would be an advantage: 

• Understanding of ML performance issues and the related technologies.
• Experience programming hardware accelerators (GPUs, TPUs etc) via ML frameworks (e.g. JAX, PyTorch) or low-level programming models (e.g. CUDA, OpenCL)
• Experience with modern compiler infrastructure and with modern distributed ML systems 
• Experience with training and using large models (>10 billion parameters)
• Interest in AI /ML and basic knowledge of AI/ML algorithms and models (e.g. Transformer)
• Coaching and mentoring qualifications / experience.
• Project management qualifications / experience.

Please include a cover letter when applying and tell us how you can make a difference to our team.