Research Engineer, Biosecurity, DeepMind
Overview
You will design and implement novel ML methods to address core biosecurity questions and support research publications and product development. You will collaborate with scientists and engineers to prototype, experiment, and scale AI research using software engineering best practices. You will influence data curation, evaluation methodologies, and infrastructure for pursuing new hypotheses. You will synthesize findings into clear reports and briefs for technical and non-technical audiences. This role sits at the intersection of frontier ML research and practical tools to mitigate biological risks, within Google DeepMind's biosecurity initiative.
Responsibilities
- Design and implement novel ML algorithms addressed to biosecurity research questions
- Prototype, experiment, and scale AI research with software engineering best practices
- Contribute to biological dataset design, evaluation methodologies, and supporting infrastructure
- Synthesize research findings into actionable reports and presentations for diverse audiences
- Collaborate with researchers and engineers to shape the research roadmap and data curation
- Publish papers and participate in broader research collaborations
Key requirements
- Bachelor’s degree in Computer Science, Machine Learning, Computational Biology, or related field, or equivalent practical experience
- 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow, PyTorch)
- problem-solving
- cross-functional collaboration
- effective communication
- deep learning applied to biological data
- TensorFlow
- PyTorch
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