AI Engineer

Title: AI Engineer
Location: Remote, United States
Compensation: Up to $250,000 + Equity
We're partnered with a mission-driven healthcare technology company working at the intersection of clinical data and AI. They're reimagining how complex clinical workflows are automated, with a focus on making high-quality healthcare data more accessible, structured, and actionable. This is a company building something genuinely novel in a space where the stakes are high and the impact is real.
This is a high-impact role where you will lead AI innovation from the ground up. You won't just be implementing models, you'll own the full lifecycle of production AI systems, define how clinical data is extracted and structured at scale, and influence the company's long-term AI direction. The work spans LLMs, computer vision, and mixed-modal approaches in a domain where rigor and accuracy are non-negotiable.
What You'll Do
Design, develop, and deploy novel AI/ML systems — with a focus on LLMs and computer vision — to recover, extract, and automate clinical data tasks across diverse data types including medical records, imaging, and clinical reports
Build robust prototypes and transition them to scalable, near-production-ready code, applying strong software engineering fundamentals throughout
Design and execute rigorous statistical validation and evaluation frameworks, defining performance metrics and ensuring models meet stakeholder-defined accuracy thresholds
Own the human-in-the-loop (HITL) lifecycle, ensuring deployed models can continuously improve over time through structured feedback capture
Partner closely with software engineering to bring proof-of-concept solutions into production, contributing to key architectural decisions along the way
Proactively identify high-impact AI opportunities across the business and define how advanced capabilities can address them
Champion best practices for documentation, experimentation, and code quality across the model development lifecycle — and potentially mentor others in doing the same
Actively evaluate state-of-the-art approaches, bringing innovative ideas and methods to the team
Apply and uphold healthcare data privacy regulations and ethical standards in all AI development work
Requirements
MSc or PhD in computer science, engineering, applied mathematics, statistics, or a related field; BSc with equivalent demonstrated experience also considered
2–5+ years of relevant experience in AI/ML engineering or data science, with increasing scope and responsibility over time
Deep hands-on Python expertise; polyglot coder comfortable across modern programming languages
Significant experience with at least one deep learning framework (PyTorch, TensorFlow, etc.) applied to LLMs or computer vision in production contexts
Proven knowledge of the healthcare data domain in at least one area: EHR/EMR, clinical imaging, clinical workflows, or clinical research
Extensive experience with modern cloud compute and storage platforms (AWS, Azure, Databricks, Snowflake, etc.)
Solid understanding of database technologies (SQL, NoSQL, etc.)
Strong familiarity with SDLC and agile methodologies
Ability to independently architect end-to-end solutions and clearly communicate how they deliver business value
Excellent written and verbal communication skills — including the ability to present complex technical concepts to non-technical stakeholders
Nice to Have
Experience with computer vision or multimodal model development
Background in clinical research, regulated healthcare environments, or medical data pipelines
Familiarity with EDC systems or clinical trial data infrastructure
Experience designing or improving HITL feedback systems in production
Exposure to AI evaluation frameworks or quality assessment tooling
If you're interested in shaping how AI systems are built, evaluated, and deployed in high-trust environments, this is an opportunity to have direct influence on both technical direction and real-world impact at a fast-growing company.

Work arrangement
Yes