Founding Research Scientist, Miscellaneous
About the Role
Sophont is a public-benefit corporation building open multimodal foundation models for medicine. Joining Sophont means you are paid to lead and contribute to high-impact medical AI research ultimately aimed to transform healthcare and life sciences.
We are looking for exceptional, high-agency ML research scientists who are passionate about using AI to build the future of healthcare. No previous background in medical AI is needed!
We especially value creative and unconventional approaches to research, and we care only about what you have built, not what your credentials are. You will have access to dedicated GPU clusters and you will work alongside top researchers in the field (both within Sophont and through collaborations with other institutions) to work on applying foundation models to the impactful field of medicine.
This is a fully remote posistion and we welcome applications from all locations. That said, we have a preference for candidates based in the US (and more specifically, the San Francisco Bay Area).
If you’re interested in working on highly impactful AI projects that could have the potential to transform and save many lives, Sophont is the company to work at.
To apply, send an email with your CV attached to hiring@sophontai.com, using the subject line '[Your Full Name] CV - Miscellaneous'
Responsibilities
- Lead, contribute to, and execute efforts to pre-train and fine-tune medical foundation models
- Writing papers and publishing at top conferences and scientific journals
- Collaborate internally at Sophont on additional foundation model projects across a wide range of medical domains (text, neuroimaging, pathology, genomics, etc.)
- Contribute to any potential external collaborations focused on medical foundation models
- Stay up-to-date with the latest advancements in AI/ML infrastructure and tools, self-supervised, RL, multimodal, medical training opportunities to enhance our model’s capabilities.
Qualifications
- 2+ years working on ML projects (training and fine-tuning ML models, especially for research projects)
- Experience with training and fine-tuning foundation models
- Experience with PyTorch
- Experience scaling up to multi-node model training (e.g., DeepSpeed, FSDP, NeMO, torchtitan)
- Publications in top-tier conferences (NeurIPS, ICML, EMNLP, CVPR, etc.), peer-reviewed journals, or code contributions to high-profile open-source repositories
- Effectively communicate ML insights and results—verbally, in writing, and through visualizations
- Self-motivated, high-agency, well-organized (e.g. keep track of your own priorities and refine the plan according to new insights), self-reliant (able to debug complex issues with minimal supervision)
- Optionally, we are also looking for (ranked in preference):
- Familiarity with the medical foundation model space
- Experience and contributions in the open-source ML ecosystem (e.g., HuggingFace, W&B)
- Experience with Discord-based public research communities (e.g., MedARC, EleutherAI, LAION)
Compensation
The expected salary range for this position is $150,000–$300,000 per year, based on a number of factors including qualifications, experience, education, and location. In addition to base salary, employees are eligible for meaningful equity incentives and a comprehensive benefits package.
Benefits and Perks
- Competitive compensation, including meaningful equity incentives
- Employees are covered by medical, dental, vision, and basic life insurance
- Employees are able to enroll in our company’s 401(k) plan with 4% Company match
- Employees will participate in workshops, hackathons, conferences and other learning opportunities
- Employees are encouraged to publish and open-source their work
- Employees have the freedom to work remotely and mostly dictate their own working hours, provided they are available during core collaboration hours
- Employees will work with a talented, hard-working, passionate, and mission-driven team focused on saving and improving lives by advancing medical AI
We are an equal opportunity employer and welcome applicants from all backgrounds.