Research Engineer, Gemini Omni Data Infrastructure

About the job

Artificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer varied learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Responsibilities

• Write product or system development code.
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 2 years of software development or ML research experience, or education equivalent credit (e.g., internships, student research, pre-graduate working experience).
• Experience conducting research to solve problems in AI or ML.
• Experience in implementing machine learning algorithms or techniques (e.g., basicautomatic differentiation) and in using machine learning frameworks (e.g., Jax, PyTorch, Triton).
• Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
• One or more scientific publication submission(s) for conferences, journals, or public repositories, including publications on machine learning or computational neuroscience.

Preferred qualifications:

• Experience with distributed storage systems, relational databases, and schema or query design (e.g., PostgreSQL, Cloud Spanner, Bigtable, Cassandra, or DynamoDB).
• Experience with large-scale data pipelines and distributed batch or streaming frameworks (e.g., Apache Beam, Spark, Dataflow, Ray, or Flink).
• Prior experience building data infrastructure, pipelines, or tooling within an ML research environment.
• Familiarity with a compiled systems/backend language (such as C++, Rust, Go, or Java) or media codecs (video, audio, image).