Senior Research Scientist, Counsel Health

• Advanced Degree: PhD degree in Computer Science, a related field, or equivalent practical experience
• Technical Expertise: Experience in coding with Python, JavaScript/TypeScript, or R
• AI/ML Specialization: Experience in agentic generative AI systems, Large Language Models (LLMs), and evaluation methodologies
• Track Record: Publications in top-tier AI/ML conferences or journals, such as NeurIPS, ICML, ICLR, or CVPR

Desirable

• We are seeking a talented, driven, and experienced Senior Research Scientist to join us in defining the future of AI + human healthcare
• As a Research Scientist at Counsel Health, you will bridge the gap between fundamental research and product innovation
• You will set up large-scale tests, deploy promising ideas quickly, and apply the latest theories to develop new and improved health-focused AI products
• From creating experiments and prototyping implementations to designing new architectures, you will work on real-world problems that span the breadth of computer science—including machine learning, natural language processing, and agentic systems—while collaborating closely with our clinical and engineering teams
• Model Evaluation: Evaluate AI models on relevant clinical tasks using both automated benchmarks and human-based assessments to ensure safety and efficacy
• Drive Research Impact: Write research papers to share findings and demonstrate impact across the team and the broader research community
• Build Health-AI Models: Build end-to-end health-focused AI models, including pre-training and post-training workflows, specifically tailored for clinical environments
• Create Novel Agentic Systems: Build agentic systems for both our patients and physicians
• For example, you might build a system that pre-drafts prescriptions for the physician based on a user’s presenting complaint, their past medical history and the suspected diagnosis
• Prototype & Simulate: Develop prototypes or run simulations to assess research impact, finalize hypotheses, and refine methodologies
• Knowledge Sharing: Help grow the research culture across teams by sharing research trends and practices within the community