Requirements

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products.
• 1 year of experience with software design and architecture.

Nice to haves

• Experience applying deep learning models to biological data (e.g., functional genomics or protein sequence data).
• Experience manipulating common life science data formats such as FASTQ, SAM/BAM, gff, BED, VCF, and PDB/CI using bioinformatics or health informatics tools.
• Domain knowledge in life sciences, computational biology, or biosecurity (including molecular biology, pathogen genomics, computational plant pathology, protein engineering, bioinformatics, or metagenomics).
• Ability to solve ambiguous and complex process and technical problems that span multiple teams and organizations.
• Ability to translate biological concepts into computational workflows and evaluation benchmarks.

What you'll be doing

• Collaborate with product leadership, external biosecurity authorities, and cross-functional teams to address biodefense challenges and define technical architectures.
• Curate specialized biological datasets, design domain-specific evaluations, and perform fine-tuning to enhance model performance on complex biological tasks.
• Develop innovative solutions and workflows using internal platforms, building advanced agents powered by models such as Gemini, AlphaFold, and AlphaGenome.
• Incorporate insights from partners and deployment data to guide future frontier model development and biological safety measures.
• Promote safe deployment practices of generative AI in bioresilience, demonstrating cutting-edge model capabilities to address critical biological problems end-to-end.

Perks and benefits

• Opportunity to work on impactful global challenges in AI and bioscience for societal benefit.
• Collaboration with interdisciplinary teams across DeepMind, Google Research, Cloud, and other Alphabet initiatives.
• Engagement in cutting-edge AI research and product innovation with access to frontier AI and generative models.
• Participation in a culture prioritizing safety, ethics, and public good.
• Varied learning opportunities and career pathways in a pioneering AI lab environment.