Senior Research Scientist

EliseAI
New York City$200k – $320kPosted 9 March 2026

Job Description

Senior Research Scientist About EliseAI At EliseAI, we're improving the industries that matter most: housing and healthcare. Everyone needs a place to live and access to quality healthcare, yet both are often harder to secure than they should be. By integrating AI agents deeply into existing workflows, we make them more efficient, reduce costs, and improve the experience for everyone. - Housing: We simplify how renters tour apartments, sign leases, submit maintenance requests, and stay connected with their property team—bringing everything they need for their home into one place. - Healthcare: We make it easy to schedule appointments, complete intake forms, and we help patients communicate with providers, so everyone can focus on health instead of paperwork. With EliseAI, organizations reduce manual work, improve accessibility, and deliver a seamless experience across essential services. We recently raised a $250 million Series E round https://www.eliseai.com/blog/eliseai-raises-250m-series-e led by Andreessen Horowitz to accelerate this mission. About The Role EliseAI is seeking world-class experts in Machine Learning and related fields to strengthen our expansive research team. We are looking for candidates with outstanding mathematical and quantitative skills, robust programming expertise, and exceptional academic credentials—including but not limited to mathematicians, theoretical physicists, and computer scientists—who are passionate about applying their knowledge to solve real-world challenges. You will be working on cutting-edge questions in machine learning and large language models, develop predictive models to enhance our AI capabilities, build controlled systematic analysis of large data, and more. As a Senior Research Scientist you will own end-to-end research initiatives that push EliseAI’s core models forward and we expect you to be able to shape the company research agenda. If you are excited about leveraging your academic background in a dynamic startup environment, we want to hear from you. Key Responsibilities - Identify open questions in tenant engagement, conversational AI, and LLM safety; turn them into road-mapped projects - Design experiments, build prototypes, run large-scale evaluations, and drive the project through to production launch - Coach junior scientists, review code, and raise the technical bar across the team - Partner with engineering, product, and GTM to translate research outcomes into customer-visible features Move at rocket speed, build something massive. We’re scaling fast, solving real client problems with precision and ambition. Here, you own your impact; full autonomy, no micromanagement, no fluff. We hire the best, expect the best, and give you the masterclass of your career. It’s hard, it’s intense, and it’s the most rewarding work you’ll ever do. If you’re hungry, driven, and ready to build something massive, climb aboard. Requirements - Ph.D. in Mathematics, Theoretical Physics, Computer Science, or a related field. - Five years of post-PhD experience (either industry of academia) - Strong preference for candidates with an established academic record - Strong foundation in machine learning algorithms, statistical analysis, and data modeling. - Proven track record of developing and implementing machine learning models, preferably in an academic or research setting - Demonstrated ability to apply analytical thinking and problem-solving skills to real-world challenges - Proficiency in programming languages such as Python, R, or similar, with experience in machine learning libraries and frameworks - Willingness to work in person at our office 4-5 days a week Why Join Growth and impact. It’s not often that you can get in on the ground floor of a funded (unicorn! https://www.eliseai.com/blog/eliseai-raises-250m-series-e) startup that’s scaling so fast. That means that instead of following a playbook, you’ll be writing it. Every single day you will be challeng ... (truncated, view full listing at source)
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