Google DeepMind
Research Engineer, Continual Learning, DeepMind
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Research Engineer, Continual Learning, DeepMind
Research-Focused Software Engineer
About the Role
At Google, research-focused Software Engineers are embedded throughout the company, allowing them to set up large-scale tests and deploy promising ideas quickly at scale. Ideas may originate from internal projects or collaborations with research programmes at partner universities and institutes worldwide.
Engaging in a mix of experimental creation, prototyping implementation, and architectural design, engineers tackle real-world challenges like:
- Artificial intelligence
- Data mining
- Natural language processing
- Hardware and software performance analysis
- Improving compilers for mobile platforms
- Core search
You maintain a strong connection to research-drive contributions to the academic community by collaborating with universities and publishing papers.
At Google DeepMind
Artificial intelligence stands as one of humanity’s most transformative inventions. At Google DeepMind, our cutting-edge AI lab brings together multidisciplinary teams to reshape AI development, addressing complex global challenges while accelerating scalable product innovation. Our AI technology serves both widespread public benefit and scientific discovery, guided by a commitment to safety and ethics.
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Our global teams foster dynamic career paths for those passionate about achieving outstanding results through collaborative and purpose-driven work. We challenge conventions across sectors, pushing boundaries in innovative ways.
Responsibilities
- Design and execute research methods at scale for compute-heavy environments
- Optimise performance through engineering practices and rigorous benchmarking
- Identify and solve key research challenges by designing, running experiments and sharing analyses to guide future work
- Bridge research and engineering disciplines by sharing expertise and insights with peers
- Develop, refine, and enhance infrastructure that supports research initiatives
Qualifications
Minimum Qualifications
- Bachelor’s degree in computer science, electrical engineering, applied science, mathematics or equivalent experience
- 2+ years of professional programming experience specifically with Python-based scientific libraries such as:
- JAX
- PyTorch
- TensorFlow
- NumPy
- Demonstrated experience developing or implementing machine learning models within production or research environments
Preferred Qualifications
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- Advanced expertise in large-scale system design or distributed systems
- Skilled in data engineering and visualisation
- Exposure to C++ or broader programming paradigms with research applications
- Academic research experience in machine learning, including publications or internships
- Technical knowledge of distributed computation for ML, especially in accelerator contexts (e.g., sharding, multi-host compute configurations)
- Strong communication skills: -Clear discussion/presentation delivery -Technical and research writing -Whiteboarding for problem analysis
Equality and Opportunity
Google is proudly committed to:
- Equal employment opportunity regardless of:
- Race
- Color
- Ancestry
- Religion
- Sex
- National origin
- Sexual orientation
- Age
- Citizenship
- Marital status
- Disability
- Gender identity
- Veteran status
Additionally, qualified applicants are considered without regard to criminal history, in line with legal requirements. See Google’s EEO Policy.
For disability accommodations during the hiring process, please complete Google’s Applicants Accommodations Request Form. Help us make this process inclusive!
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