Full-Time

ML HW-SW Co-Design Silicon Tech Lead Manager

DeepMind

DeepMind

1-10 employees

AI research organization pursuing safe AGI

No salary listed

Mountain View, CA, USA

In Person

Category
Software Engineering (1)
Required Skills
Machine Learning
Requirements
  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
  • 10+ years of experience in silicon architecture, design, validation, or product development.
  • Proven track record of technical leadership and successfully delivering complex silicon projects (tape-outs) to production.
  • Deep expertise in at least one core silicon discipline (e.g., RTL, PD, DV) and strong familiarity with the entire ASIC flow.
  • Experience with managing cross-functional silicon projects, including schedule, scope, and execution, and also managing silicon vendors and other external partners.
Responsibilities
  • Direct Technical Contribution (IC): Directly contribute to the codebase and technical strategy. IC focus can be one specific silicon engineering discipline, or spanning the program needs more broadly.
  • Technical Team Leadership: Lead a small team of ML silicon engineers across logic design, physical design, interconnect, and power.
  • Architectural Alignment: Drive team cohesion by synthesizing fragmented technical opinions into a single, high-quality execution plan.
  • HW-SW Strategy: Partner closely with the ML software team to define requirements for next-generation ML accelerators.
  • Execution Management: Oversee technical execution across a virtual team including Google-internal and external partners.
Desired Qualifications
  • Master's or Ph.D. in a related field.
  • Experience leading and managing teams across the full silicon development cycle, from RTL to bringup.
  • Experience with high-performance compute IPs (e.g., GPUs, ML accelerators).
  • Knowledge of high-performance and low-power architectures for ML acceleration.
  • Excellent communication, and leadership skills.

DeepMind conducts research in artificial intelligence to advance general problem-solving capabilities with safety and ethics guiding every project. It develops AI systems and learning algorithms that can tackle complex tasks, such as diagnosing eye diseases, reducing data center energy use, and predicting 3D protein shapes. These products work by learning from large datasets and optimizing models to perform specialized tasks, often through deep neural networks and reinforcement learning, then deploying the resulting systems to assist scientists, doctors, and engineers. What sets DeepMind apart is its emphasis on rigorous fundamental research published in top journals, a strong safety/ethical framework, and collaboration on real-world scientific challenges, rather than just commercial applications. The company’s long-term goal is to solve intelligence and build more general, capable problem-solving systems that can help society address major scientific and humanitarian problems.

Company Size

1-10

Company Stage

Acquired

Total Funding

$533M

Headquarters

Thessaloníki, Greece

Founded

2010

Simplify Jobs

Simplify's Take

What believers are saying

  • GraphCast excels in extreme weather prediction, partnering with disaster agencies.
  • AlphaFold collaborates with DNDi on Chagas and Leishmaniasis therapeutics.
  • Open GraphCast deployment since September 2024 enables enterprise licensing.

What critics are saying

  • Top AI talent exits DeepMind due to Google merger bureaucracy.
  • Isomorphic Labs secures Eli Lilly and Novartis drug discovery deals.
  • NVIDIA's PhysicsNeMo reimplements GraphCast, commoditizing the technology.

What makes DeepMind unique

  • AlphaFold predicts protein structures, catalyzing biology progress since 2021.
  • GraphCast delivers 90% accurate 10-day weather forecasts in under one minute.
  • AlphaGo defeated Go champion Lee Sedol in 2016 using reinforcement learning.

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