Senior Machine Learning Scientist - AI Virtual Cells

Join Rivercell as a Senior Machine Learning Scientist, where you will contribute to the development of AI virtual cells, a groundbreaking project in techbio. You will implement, train, and test AI models, contribute to the technical roadmap, and collaborate with biology and engineering teams. This role offers a competitive salary, equity package, and exciting opportunities for personal and professional growth.

Please let us know in your application if you specifically have experience with one or several of the following:

About Rivercell

You have strong engineering practices: versioned data, pinned dependencies, reproducible analyses, documented decisions

You have a make-it-work-make-it-better mentality: comfortable shipping the first version end-to-end on a pre-seed timeline, choosing pragmatism over elegance, and returning to harden the parts that proved load-bearing

Responsibilities

• Implement, train, and test AI virtual cell models, contributing to the technical roadmap and research priorities.
• Identify and harmonize useful cellular datasets with the biology team, and develop benchmarks and evaluation tools relevant to industrial users.
• Contribute to preprints/publications, conference publications, and public benchmark releases, and present findings to various audiences.

Requirements

• You have a PhD in machine learning, computational biology, or an adjacent field, or equivalent industry research experience
• You have hands-on experience training models on single-cell or perturbation data
• You have at least one first-author publication in a relevant venue (Nature Methods / Cell Methods family, NeurIPS / ICLR / ICML main track or workshop, or a preprint with demonstrable adoption in the field)
• You have strong PyTorch fluency, including distributed training on multi-GPU or multi-node setups
• You are comfortable with the single-cell data engineering ecosystem and its real-world messiness
• You have strong scientific communication skills, written and spoken: write papers, present results to AI-lab and pharma audiences, and translate technical claims into investor-facing material
• Experience with transformer or diffusion architectures applied to cellular data

Familiarity with cellular morphology and image-feature pipelines

• Benchmark design experience, including a sense of the politics of running a public leaderboard
• Working knowledge of the current AI virtual cell literature and an opinion about where it is going
• Experience in working in a fast-paced start-up environment

Preferred

• Foundation-model pretraining, fine-tuning, or evaluation at scale