Software Engineer, Platform

Snapshot

We’re looking for someone who is passionate about building infrastructure and products to help enable research at scale. No machine learning experience is required for this role!

About us

DeepMind's mission is to "Solve intelligence to advance science and benefit humanity".

The goal of the Platform team is to make all of DeepMind fast and effective through products, tools, libraries, frameworks, services, and to co-deliver key technical innovations to unlock AGI. We are a core group of ~70 SWEs and other technical roles who work with other teams across the company to provide and advance our state-of-the-art technological infrastructure. We prioritise projects with broad & strategic impact across DeepMind, while also providing focused capabilities to accelerate key DeepMind efforts.

The Platform team plays a critical role in the mission of DeepMind in multiple ways. In the simplest form, improvements in our experimentation workflow turn into super-linear impact on research productivity. On the other hand, we invest time & energy into new foundational engineering capabilities to support DeepMind’s ambitious plans and world-class scientific discoveries.

Non-exhaustive examples of the types of work in the Platform team:

• Infrastructure to leverage DeepMind’s massive computational resource pool to maximum efficacy (consisting of TPUs, GPUs, and CPUs - xx% of the production fleet).
• Platforms for testing and evaluating ML algorithms in various simulated environments.
• Systems for easily logging, storing, searching, and analysing large quantities of experiment data.
• Project management systems specialised for organising research at scale.
• Customising ML frameworks & libraries at the language & compiler level for DeepMind’s use cases.

The role

We're looking for hardworking software engineers who are interested in creating and enhancing tools and services to help research flourish! You’ll join an inspiring and collaborative environment, working on ground-breaking technology with potentially extraordinary impact.

As a member of the Platform team, you’ll work alongside experienced SWEs, Program Managers, and UX experts on tools that will make a material impact on the workflows of your colleagues. Your users will be other DeepMinders, so you’ll get to work closely with helpful, motivated collaborators who will give you immediate feedback and help you iterate rapidly.

Within this broader engineering team, we’re currently growing our efforts in the following projects:

• Tech for DeepMind Operations: Enable DeepMinders across the organisation (not just research) by creating automated solutions to day-to-day workflow problems ranging from data pipelines, scheduling systems, to public websites. This project involves a large diversity of tech stacks and lots of direct interaction with users across the company.
• Hardware Accelerators & Programming Abstraction: demonstrating modern hardware accelerators is key to attain ML breakthroughs, so we work hard to make it easy to use these devices efficiently and at scale. Projects in this area involve understanding and enhancing compiler & runtime optimisations, building better programming abstractions, and in general helping our researchers turn their ideas into efficient/accelerated computer programs at scale.
• Experiment Data Analysis and Human Interaction: Enable DeepMinders and human participants to interact with our agents and running experiments at scale. The projects in this area involve latency-sensitive network connections, storage and indexing of large volumes of experiment data, and interactive rendering toolkits.