Abridge is building an AI platform for clinical conversations, to solve the administrative burdens of medicine, freeing clinicians to focus on patient care. Our technology is rapidly expanding to support clinicians through a richer suite of interactions—helping them to make better informed decisions and to navigate medicine’s financial processes. Abridge improves patient outcomes and access to care, enables clinicians to focus on what matters most, and lowers costs for health systems.
Requirements
- 7+ years of experience in machine learning/NLP, with a strong track record of impactful publications and deployed systems.
- 4+ years of experience as technical lead for a project of 4 or more individuals.
- 2+ years of direct management experience, managing Researchers and Applied Scientists.
- Deeply technical, with expertise across NLP and LLMs—e.g., pre-training/post-training/SFT/RL, retrieval augmented generation (RAG), reasoning capabilities, multilinguality, multimodality, synthetic data generation, noise robustness, judges, and evaluation.
- Have fluency with libraries for scientific computing (e.g. SciPy, Numpy) and machine learning (e.g., PyTorch, TensorFlow, Scikit-learn, Pandas).
- Up-to-date on the latest in NLP and ML research, with excitement for continuous learning.
Responsibilities
- Lead, mentor, and scale a high-impact team of NLP/ML researchers, fostering a culture of technical rigor, creativity, and scientific excellence.
- Set R&D strategy that aligns with company priorities in areas like: Clinical NLP, summarization, and dialogue understanding.
- Set R&D strategy that aligns with company priorities in areas like: Agentic capabilities, retrieval-augmented generation, reasoning, and tool-use.
- Set R&D strategy that aligns with company priorities in areas like: Multimodal and multilingual algorithms.
- Set R&D strategy that aligns with company priorities in areas like: Reinforcement learning, preference optimization, and reward modeling.
- Set R&D strategy that aligns with company priorities in areas like: Robustness, safety, and evaluation of LLM-powered systems.
- Partner with engineering teams and clinicians to operationalize novel algorithms into clinician-facing workflows, optimizing both quality and efficiency.
Other
- Grow talent pipelines by recruiting world-class researchers and nurturing career development through coaching and mentorship.
- Balance long-term vision with near-term impact, ensuring research not only advances the field but also translates into product-grade systems.
- Ensure safety and robustness in deployment, shaping the standards for evaluation in clinical AI.
- Represent Abridge in the global ML/NLP research community through publications, conference presentations, and industry/academic partnerships.
- Comfortable bridging research, product, and engineering, translating novel ideas into robust, scalable systems that deliver real-world impact. You think about how research translates into user impact, and have experience aligning scientific direction with business and product goals. You have shipped models, designed benchmarks, and debugged real-world failures (from data drift to brittle eval pipelines).
- A thoughtful leader: you foster a feedback-rich culture, set a high bar for scientific rigor, and empower your team through mentorship, clear vision, and mutual trust.
- Motivated to work in a fast-paced, collaborative environment where your team’s science has direct clinical impact.
