Software Engineer, Model Scaling

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.

Snapshot

We’re looking for someone who is passionate about enabling our world-class AI researchers to break new ground by effortlessly scaling their models. No machine learning experience is required for this role!

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

The rising use of large language models (LLMs) demands efficient and performant solutions for training and serving models. As a member of the Model Scaling team you will enable ML users to scale their models and optimize their performance.

We're looking for passionate software engineers with a keen interest, but not necessarily prior experience, in

• compilers
• high-performance computing
• ML models

You’ll join an inspiring and collaborative environment, where you’ll work alongside experienced software engineers and research scientists from a diverse set of backgrounds. You’ll be working closely with AI researchers and deliver solutions to enable them to advance the state of the art in AI by effortlessly scaling their models.

The project involves working in various areas which you will be able to explore and contribute to:

• compiler technologies built with MLIR
• user APIs for Python/JAX
• cost modelling of large-scale ML accelerators and supercomputers
• data-driven optimization techniques (e.g. search, reinforcement learning, etc)

Key responsibilities:

Depending on your skills and interests, some of your responsibilities will be:

• Improve efficiency of ML models on hardware accelerators
• Profile models to identify performance bottlenecks and opportunities
• Write low-level code targeting hardware accelerators
• Implement model partitioning techniques to efficiently partition models across accelerators
• Identify the best hardware setup for deploying a diverse set of models
• Work closely with ML compiler teams to improve efficiency
• Design and implement optimisations for distributed serving systems, e.g. reducing network transfers and redundant computations

About You

You're an engineer with a strong interest in contributing to the advancement of AI. You're excited by the challenge of optimizing performance and enjoy collaborating effectively within a team.

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

• Interpersonal skills, such as discussing technical ideas effectively with colleagues
• Excellent knowledge of either C++ or Python
• Experience with object-oriented programming languages
• Solid understanding of algorithm and data-structure design
• An interest in Google DeepMind's mission

In addition we are looking for experience with at least two of the following:

• Experience programming hardware accelerators (GPUs, TPUs etc) via ML frameworks (e.g. JAX, PyTorch) or low-level programming models (e.g. CUDA, OpenCL)
• Profiling software to find performance bottlenecks
• Leveraging compiler infrastructure to improve performance on hardware
• Distributed ML systems optimization
• Training and using large models (>10 billion parameters)
• Interest in AI and basic knowledge of AI algorithms and models (e.g. Transformer)

Application deadline: 4th February