AI Research Scientist

About Us

Our mission is to make healthcare reimbursement transparent and fair (/phare), so providers can spend more time caring for patients and less time haggling over costs. We specifically focus on the most complex AI challenges that require novel R&D, with a team that blends AI researchers and engineers with clinicians, and payment experts. Backed by General Catalyst, we’re scaling quickly - join us!

The Role

You’ll own the architecture, training, and optimization of large-scale transformer-based pipelines, wrangling PyTorch, GPUs, and distributed infrastructure to push forward SOTA. Think “research lab rigor” fused with “startup shipping speed.” Expect to:

• Design and iterate on new transformer and hybrid text architectures; scale promising ideas across multi-GPU / multi-node clusters with PyTorch.

• Drive the research roadmap: propose experiments, benchmark against state of the art, and publish or open-source meaningful advances.

• Build retrieval-augmented generation (RAG) pipelines and lightweight agent workflows, balancing accuracy, latency, and cost.

• Convert research prototypes into reliable services with CI/CD, monitoring, and rollback.

• Partner with product and design to translate model capabilities into intuitive user experiences.

Who We’re Looking For

• 3+ years training large transformer models in Python/PyTorch at scale.

• Peer-reviewed publications or significant open-source work in text modelling.
  Proven end-to-end ownership: architecture → distributed training → deployment.

• Fluency with Lightning/FSDP, Pytorch, Hugging Face, WandB, Ray/Kubeflow, Docker

• Deep expertise in text modelling; clinical-text knowledge not required.
  

Bonus points

• RLHF or policy-optimisation methods (PPO, TRPO, DPO).

• Familiarity with healthcare ontologies or claims data.

Benefits

• Top-of-market compensation (salary + equity)

• Flexible PTO & hybrid culture (SoHo HQ 3 days/wk; exceptional remote considered)

• Mission-driven, collaborative team

• Twice-yearly offsites to align, build, and celebrate.

Hiring Process

1. Initial application.

2. Intro call: Discuss your background, career goals, and our mission.

3. 2 x Technical interviews: A programming or system design exercise focused on real-world data challenges.

4. Referees: We ask for 2 referees who can speak to your professional/technical work

5. Culture interview: Ways of working, and a chance to ask questions

6. Offer