Founding Research Scientist - Pathology Foundation Models
To apply, send an email with your CV attached to hiring@sophontai.com, using the subject line "[Your Full Name] CV - Pathology Foundation Models".
About Sophont
Sophont builds open, universal medical AI that understands pathology, neuroimaging, clinical text and more, empowering clinicians and researchers worldwide.
We are a public-benefit corporation driven by a mission to build AI models and applications to advance healthcare and benefit humanity. Together with MedARC, our open-source Discord community, we are dedicated to open science and developing frontier AI models for medicine transparently. We already have a strong track record, having published open-source well-cited research in NeurIPS, ICML, CVPR, Nature Biomedical Engineering, and more. As part of our radically transparent approach, you can already join our public meetings to see how we conduct research at Sophont and MedARC.
Sophont is a rare early-stage company with both world-class technical leadership and a mission that matters. Joining Sophont means you are paid to lead and contribute to high-impact medical AI research that will transform healthcare and life sciences.
Our team is composed of leaders in their respective domains, backed by investors from Google (Jeff Dean, Logan Kilpatrick), W&B (Lukas Biewald), Hugging Face (Clem Delangue), Kindred Ventures, Upfront Ventures, and more.
How We Build
Sophont functions differently than other startups. There is no clean separation between thinking and doing. The same people deciding what should exist are the ones building it.
A large part of that work happens in the open. Through MedARC, an open science Discord community, Sophont staff lead groups of highly motivated contributors running experiments, testing ideas, and pushing new directions forward continuously. It is closer to a live research lab than a traditional team.
About the Role
We are seeking an exceptional Research Scientist to lead our pathology foundation model strategy, setting the direction for how these models are built, evaluated, and translated into real clinical and pharma applications. This role is not limited to improving models in isolation, but defining how foundation models interface with biological context, multimodal data, and downstream decision-making systems.
We have previously built and released OpenMidnight, a state-of-the-art open-source pathology foundation model trained on only twelve thousand slides. This role will significantly expand upon the research behind OpenMidnight.
This is an early startup role, meaning you will contribute to building the company from the ground up. It is an opportunity to operate with direction, ownership, and impact across both research and deployment, turning new ideas into working systems that hold up in real-world settings.
What You'll Do
- Lead, contribute to, and execute efforts to pre-train and fine-tune self-supervised and multimodal vision models on pathology and multimodal data
- Build and experiment with modern architectures optimized for biomedical applications
- Write papers and publish at top conferences and scientific journals
- Build distributed training and inference pipelines, experiment tracking systems, and evaluation frameworks
- Collaborate internally at Sophont on additional foundation model projects across a wide range of medical domains, including text and genomics
- Lead MedARC contributors assisting in foundation model development
- Stay up to date with advances in AI and ML infrastructure, self-supervised vision, and multimodal training to expand our model capabilities
- Contribute to publications in top-tier ML and biomedical venues including NeurIPS, ICML, ICLR, Nature, and Cell
What We're Looking For
- Experience training self-supervised vision models such as DINO, MAE, or SimCLR
- Strong publications or technical blog posts that demonstrate impactful work, including conference papers, journal articles, or open-source write-ups
- Strong command of modern architectures including transformers, attention mechanisms, state-space models, and mixture-of-experts systems
- Experience working on GPU clusters and ML infrastructure such as Kubernetes, SLURM, or equivalent systems
- Strong software engineering fundamentals
- Clear communication skills across engineering and scientific audiences
Preferred
- Experience with biomedical foundation models
- Background in oncology, cancer biology, or drug development
- Experience with multimodal learning and cross-modal architectures
- Familiarity with regulatory considerations in healthcare AI including FDA and HIPAA contexts
- Experience contributing to the open-source ML ecosystem such as Hugging Face or Weights & Biases
- Experience with Discord-based public research communities such as MedARC, EleutherAI, or LAION
- Experience in a startup environment
Location
This role is fully remote with the ability to mostly dictate your own working hours, provided you can attend core collaboration meetings.
Compensation
The salary range for this role is $100,000-$300,000 USD per year. Benefits include meaningful equity, OpenAI and Anthropic subscriptions, a 401(k) with 4% match, medical, dental, vision, and basic life insurance.
Employees are encouraged to publish and open-source their work and to participate in workshops, hackathons, and conferences.
We are an equal opportunity employer and welcome applicants from all backgrounds.