Research Engineer, Chip Verification

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Snapshot

Artificial Intelligence could be one of humanitys most useful inventions. At Google DeepMind were 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.

At Google DeepMind youll have the opportunity to revolutionise AI by applying stateoftheart AI to Chip Design. We develop research breakthroughs that impact all aspects of the Electronic Design Automation (EDA) process to significantly reduce the time to market of Googles products and services.

About Us

Artificial Intelligence could be one of humanitys most useful inventions. At Google DeepMind were 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.

About the Team:

We develop and apply stateoftheart AI methods and models to Chip Design and work closely with research and product teams across Google.

Our team is composed of research scientists research engineers and software engineers that have already had a big impact on real products via research breakthroughs. We work on lighting the path of new ideas that can become new products. We work closely with hardware engineers architects and ML model developers to generate novel ideas and bring them to products.

We are core contributors to MLIR which we use as a core technology to represent abstractions from models to transformations hardware and simulators. The mission of our team is to enable near infinite compute at near zero cost. This implies working across the entire software and hardware stack to discover opportunities for optimization and create AI basedtechnologies that improve the efficiency of training and serving AI workloads.

At Google DeepMind weve built a unique culture and work environment where longterm ambitious research grounded in real problems can flourish.

The Role

As part of our team at Google DeepMind youll have opportunities to advance AI for Chip Design to enable breakthrough capabilities and pioneer nextgeneration products in collaboration with teams spanning major Product Areas.

There are many fundamental research and transformative product landing opportunities including but not limited to:

• Bring the most advanced ML models and technologies to chip design.
• Develop breakthrough technologies that will have a big impact for Google products and for the whole chip design industry.
• Enable efficiency across the entire AI learning stack.
• Solve some of the most complex tasks in automating chip design: hardwaresoftware codesign for ML models hardware generation and verification RTL optimization and system design.
• Engage and work in a fast paced rapidly shifting environment demonstrating flexibility and the ability to bring clarity in ambiguous problem spaces.

Key Responsibilities

• Contribute and drive ML for hardwaresoftware codesign.
• Contribute and drive hardware generation technologies using ML techniques traditional compilerbased transformations and novel program generation techniques such as program synthesis and constraintbased programming.
• Identify unsolved impactful research problems in chip design inspired by current and future real world needs.
• Collaborate with model developers software developers and hardware architects to ensure generated designs are correct and efficient.
• Amplify impact by generalising solutions in opensource code publications and education.

About You

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

• Ph.D. in Computer Science or related quantitative field or B.S./M.S. in Computer Science or related quantitative field with 5 years of relevant experience.
• Experience in codegeneration technologies: intermediate representations program synthesis programming with constraints.
• Experience in Machine Learning (ML) especially on ML for hardware ML for compilers or ML for optimization.

In addition the following would be an advantage:

• Experience with MLIR and in particular dialects specialized for hardware synthesis e.g. CIRCT XLS and similar.
• Experience with JAX TensorFlow PyTorch or similar.
• Experience or interest in hardware verification technologies formal methods theorem proving and hardware testing methodologies.
• Selfdirected engineer/research scientist who can drive new research ideas from conception experimentation to productionisation in a rapidly shifting landscape. Excel at teamwork and crossteam collaborations.
• Strong research experience and publications in relevant fields: hardware synthesis and verification machine learning or codegeneration.

The US base salary range for this fulltime position is between $166000 $244000 bonus equity benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Application deadline: May 31st 2025

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