Research Scientist

About the job

Responsibilities

• Own research initiatives end-to-end, including problem formulation, experimental design, modeling, and evaluation.
• Develop novel architectures, training methods, and objectives leveraging longitudinal patient data.
• Work on verifiable reinforcement learning, mid-training, and post-training of foundation models.
• Design rigorous evaluation methodologies to assess model reasoning, correctness, and clinical relevance.
• Make and own tradeoffs between model capability, interpretability, and verifiability in high-stakes settings.
• Collaborate with clinicians and engineers to define meaningful problem formulations grounded in real-world workflows.
• Partner with ML engineers to ensure research translates into deployable systems.

Requirements

• Strong foundation in machine learning, deep learning, or a related technical field.
• Track record of driving ML research or novel modeling work from idea to validated results.
• Experience working on ambiguous research problems with limited prior art.
• Hands-on experience with PyTorch or similar frameworks.
• Ability to operate independently in high-ambiguity environments with minimal guidance.
• Strong technical judgment to identify meaningful problems, design appropriate approaches, and evaluate results rigorously.
• Comfort working in a fast-moving, early-stage environment.
• Experience working on systems where decisions have real-world consequences (e.g., healthcare, finance, infrastructure).

Benefits

• Competitive compensation, including meaningful equity
• Medical, dental, and vision insurance for employee and dependents
• Flexible PTO policy
• Paid parental leave
• Fertility and family-building stipend through Carrot