Research Scientist​/Engineer: Healthcare

Welcome systems thinkers. System builds software to help the world see and solve anything as a system, starting in healthcare. We are a Public Benefit Corporation driven by purpose and shaped by values. We hire systems thinkers who are motivated by our purpose, share our values, and have the skills to advance our mission.

Overview

We are seeking a highly skilled Research Scientist/Engineer to join our team. The ideal candidate will have a strong technical background in machine learning, extensive work experience with clinical healthcare data, and a working knowledge of producing Real-World Evidence using data from Electronic Health/Medical Records. You will work closely with other engineers and scientists on the team to design and implement solutions to difficult applied problems.

This is a role for someone who is ready to make an impact on the future of science and data. This person will report to the Director of Engineering.

• Work on cutting edge solutions in healthcare data modeling and contribute to innovation in AI/ML for Healthcare
• Keep abreast of the latest developments in the field of machine learning, and work with engineers to incorporate these developments into our technology stack
• Develop leadership skills and help to foster a culture of collaboration and continuous learning
• Influence culture and shape a rapidly growing startup
• Design and implement benchmarking frameworks to evaluate the performance, robustness, and efficiency of algorithms, models, or systems.
• Develop and maintain evaluation metrics tailored to specific domains (e.g., NLP, computer vision, multi-modal systems, distributed systems).
• Collaborate with cross-functional teams (researchers, engineers, product managers) to define success criteria and validate new methods or architectures.
• Lead or contribute to experimental design, A/B testing, and statistical analysis of large-scale system behaviors.
• Analyze performance trade-offs, failure cases, and corner scenarios to improve model and system quality.
• Author internal technical reports and, where appropriate, contribute to peer-reviewed publications or open-source benchmarks.
• Stay current with advancements in evaluation methodologies, datasets, and benchmarking best practices in your field.

• M.S. or Ph.D. in Computer Science, Electrical Engineering, Statistics, or a related field; or equivalent industry experience.
• Expertise in at least one major programming language (e.g., Python, C++, or Java), as well as strong experience with relational databases
• Experience with common machine learning frameworks, NLP and LLM toolkits
• Experience applying machine learning models to very large, complex datasets
• Strong expertise in scientific methods, experimental design, statistical analysis, and evaluation methodology.
• Experience with benchmarking tools, evaluation libraries, and relevant frameworks (e.g., Hugging Face, OpenAI Evals, MLPerf, Sci Kit-learn, Tensor Flow Model Analysis, or custom pipelines).
• Familiarity with ML/DL model evaluation (e.g., accuracy, F1, BLEU, ROUGE, fairness metrics, latency) and human-in-the-loop processes
• Excellent communication and collaboration skills, with a proven ability to communicate results clearly to technical and non-technical audiences.
• Understanding of how to push your code “beyond the notebook”, i.e. writing production quality code, API development, containerization, inference at scale.
• Strong problem-solving abilities and attention to detail
• Ability to be flexible, rational and open-minded

• Experience generating real-world evidence from electronic medical record (EMR) data using LLM-based workflows (entity resolution, normalization, extraction)
• Startup experience

Compensation: $160,000 - $190,000

We aspire to help the world see itself differently and build a more responsible and values-driven model of a tech company. We are backed by top-tier VCs in Silicon Valley and New York and leading angel investors and founded by the former VP Data  learn more about what motivates our social mission, we invite you to read our blog here.

We believe in the power of autonomous, interdisciplinary, and diverse teams; in…