Senior Machine Learning Scientist - AI Virtual Cells

Rivercell; Paris; On-site; EUR 110,000 - 150,000; Full time

Benefits offered by this job

Competitive salary & equity

Growth opportunities

Cutting-edge biotech project

Job summary

Rivercell seeks a Senior Machine Learning Scientist to help build and scale its AI Virtual Cell (AIVC) models in a collaborative biotech startup. You will influence the scientific direction, contribute to the modeling agenda, and help recruit the ML team.

You will join an interdisciplinary team spanning genetics, AI, software, biology, and bio-lab automation, contributing to the project from its inception and pushing the field forward with reproducible research and public benchmarks.

Qualifications

• PhD or equivalent industry research experience in ML/biology.
• Hands-on experience training models on single-cell or perturbation data.
• At least one first-author publication in a relevant venue or demonstrable adoption in the field.

Responsibilities

• Contribute to the technical roadmap and research priorities through literature reviews and experiments.
• Identify and harmonize useful cellular datasets with the biology team.
• Implement, train, and test AI virtual cell models.

Skills

PyTorch

Distributed training

Single-cell data

Engineering practices

Scientific communication

Leadership

Education

PhD in ML/Computational Biology

Tools

PyTorch

Job description

We are looking for a Senior Machine Learning Scientist to work on the development of our AI Virtual Cell (AIVC) models. As an early member of the AI team, you will contribute to the modeling agenda, the implementation, and be accountable for what we ship. You will work alongside the founding team and contribute to the scientific direction, see your work impact the company's roadmap, and help recruit the ML team.

You will work within an interdisciplinary team spanning genetic engineering, AI and software, bio-laboratory automation, optics, electronics, and biology. You will be an integral part of an ambitious and exciting startup project from its inception.

• Contribute to the technical roadmap and research priorities through literature reviews and experimental findings.

• Identify and harmonize useful cellular datasets with the biology team.

• Implement, train, and test AI virtual cell models.

• Design and run empirical studies to assess the value of different data and modeling approaches.

• Develop benchmarks and evaluation tools relevant to industrial users.

• Maintain reproducible training code and analyses for the team and external collaborators.

• Debug data pipelines and improve model performance and compute efficiency with engineering colleagues.

• Contribute to preprints, conference publications, and public benchmark releases.

• Present findings and help respond to questions from reviewers and collaborators.

• Support technical material for partners and fundraising.

• Opportunity to work on a cutting-edge project in the field of biotech

• Opportunity to join an ambitious team and impactful startup among the first employees

• Competitive salary and equity package

• Exciting opportunities for personal and professional growth within the team

You have a PhD in machine learning, computational biology, or an adjacent field, or equivalent industry research experienceYou have hands-on experience training models on single-cell or perturbation dataYou 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 setupsYou are comfortable with the single-cell data engineering ecosystem and its real-world messinessYou have strong engineering practices: versioned data, pinned dependencies, reproducible analyses, documented decisionsYou 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 materialYou 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‑bearingPlease let us know in your application if you specifically have experience with one or several of the following:Experience with transformer or diffusion architectures applied to cellular dataFoundation-model pretraining, fine‑tuning, or evaluation at scaleFamiliarity with cellular morphology and image‑feature pipelinesBenchmark design experience, including a sense of the politics of running a public leaderboardWorking knowledge of the current AI virtual cell literature and an opinion about where it is goingTeam leadership is a plusExperience in working in a fast‑paced start‑up environment