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SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.
At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
We are looking for a Bioinformatician with deep experience in the training and application of deep learning models, especially but not limited to genomics, transcriptomics, spatial transcriptomics, and related fields. As a member of the Large Quantitative Model (LQM) team, you will develop completely new computational tools to reshape drug discovery.
What You’ll Do- Develop and apply deep learned models to predict genomic and transcriptomic profiles, including after perturbation by drug molecules.
- Drive curation and use of high-quality datasets, such as single-cell RNA-seq datasets.
- Work with a cross-functional team of experts to computerize drug discovery.
- Write patents, research papers and technical documents. Participate and present at international conferences.
- Reshape drug discovery, advance machine learning, and protect humanity from disease.
- Ph.D. in a field setting you up to work on deep learning models for genomics, transcriptomics, and biological pathway modeling: computational biology, bioinformatics, computer science, applied math, etc.
- 2+ years working on deep learning for biopharma in an industry context.
- Experience in training, applying, and optimizing contemporary deep learning models, including generative models, as demonstrated by:
- Publications and/or presentations
- Contributions to software projects
- Experience applying deep learning models to problems in biopharma: genomics, transcriptomics, spatial transcriptomics, and/or related fields such as structural biology.
- Software skills: advanced proficiency with Python, with related software ecosystem tools (i.e. Git, Docker, Kubernetes, etc), and contemporary deep learning and informatics terms (i.e. R, Pytorch, etc)
- Excellent communication skills
- Relevant postdoctoral training
- Experience in long-context sequence modeling
- Direct experience in drug discovery or development
- Experience running deep learning workloads on GPU clusters at large scale
- Experience working on cloud
- Contributions to open source repositories
The US base salary range for this full-time position is expected to be $192k - $269k per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.
