Product Engineer, AI / ML

Thesis•New York, NY

3h•$200,000 - $250,000•Hybrid

About The Position

Thesis is building the AI-powered care team platform for infinitely scalable clinical capacity. We radically increase access and improve quality of care by combining AI agents with clinical experts to take on high-impact clinical operations and care management activities for healthcare organizations. We’re based in NYC, are growing rapidly, and are backed by $60 million in funding from Oak HC/FT, CRV, Black Opal Ventures, and experienced C-level healthtech angel investors. We are looking for a highly capable Product Engineer to help build and scale Thesis’s AI Care Team platform. This is a broad-scope, hands-on engineering role for a technical builder with strong ML fundamentals, production experience, and a product-oriented mindset. As an early member of the engineering team, you will play a critical role in designing, training, deploying, and operating the ML systems that power Thesis’s AI coordinator.

Requirements

ML and data depth: 3+ years of experience ingesting, structuring, and analyzing diverse data sources, with strong proficiency in Python, SQL, and data tooling (e.g., pandas or equivalent).
Production AI experience: Hands-on experience building and operating NLP and/or LLM-powered systems in production, including frameworks such as spaCy, LangChain, and extensive LLM API usage.
Pipeline expertise: Significant experience designing and maintaining data and ML pipelines in production environments.
Cloud and infrastructure fluency: Experience working in AWS environments, including containerized workloads and orchestration for training and inference.
Healthcare familiarity: Experience working with healthcare data and an understanding of the constraints of regulated environments, or strong motivation to develop this expertise.
Cross-functional communication: Ability to collaborate effectively with engineers, product leaders, and clinical stakeholders.
Ownership mentality: Demonstrated success operating in early-stage or high-growth environments with broad technical responsibility.
Full-stack capabilities: Comfort contributing beyond core ML work, including APIs, system design, or frontend-adjacent development when needed.
NYC-based: You are based in New York and excited to be in-office ~3 days per week.

Responsibilities

Build and own AI systems end-to-end: Ingest, structure, and analyze large volumes of unstructured healthcare data, and design production-grade data and ML pipelines for both training and inference.
Develop NLP and LLM-powered features: Design, evaluate, and deploy models using modern NLP frameworks and LLM APIs, with a strong focus on real-world performance and reliability.
Operate at production scale: Architect and maintain cloud-based ML workflows in AWS, including containerized services and orchestration for data processing, training, and inference.
Continuously improve model quality: Monitor, test, and iterate on model accuracy, robustness, privacy, and safety within live clinical workflows.
Contribute across the product: Collaborate across the stack—from APIs and backend systems to product UX and workflow design—to deliver cohesive, AI-driven features.