AI Engineer | Computer Vision + LLMs

Role overview Own the AI work behind a remote eye care platform, turning smartphone images and longitudinal patient records into useful clinical insight. The role spans an existing ocular imaging pipeline and new language model systems, with responsibility for setting technical direction and validating results with clinicians.

Responsibilities - Take ownership of the current eye image pipeline and improve its reliability for images captured by patients in varied settings. - Train, evaluate, and deploy vision models using clinical data, accounting for differences in lighting, focus, framing, skin tone, and device hardware. - Work with optometrists and ophthalmologists to define ground truth and assess model performance. - Build language model and agentic systems that summarize patient histories, flag meaningful changes for clinicians, and support patient check-ins and treatment adherence. - Apply retrieval, structured outputs, tool use, and other LLM techniques, with careful evaluation suited to clinical use. - Set AI technical direction in collaboration with the engineering team and clinicians.

Requirements - Practical experience building with modern LLMs, including prompting, evaluation, retrieval, and tool use; familiarity with fine-tuning where appropriate. - Strong engineering skills and ability to take models into production. - Ability to turn an ambiguous clinical question into a defined machine learning problem. - Careful evaluation habits and a willingness to question model results, especially when they may affect patient care. - Comfort using AI tools in development and taking responsibility for reviewing their output.

Nice to have - Experience in medical or ophthalmic imaging, clinical machine learning, on-device ML, or electronic health record integrations. - Relevant projects, papers, repositories, models, or shipped systems to share.

Benefits and work setup - Full-time, hybrid role in New York City. - Competitive salary and equity.