- Be a key cross-functional team member, and close collaborator to product teams. Make significant contributions from translating research into benchmarks to co-authoring product roadmap.
- Design and build evaluation systems that test LLM capabilities in the healthcare domain, and interpret and communicate results.
- Run experiments to determine how different prompting techniques affect results on internal and industry benchmarks.
- Improve the tooling that is used internally to implement, run and analyze evaluations.
- Design internal benchmarking and regression testing capabilities that capture model accuracy, safety and utility.
- Bachelor's or Higher Degree in Computer Science, or related technical discipline AND significant Python programming experience / machine learning research.
- Deep experience building with and around LLMs, and experience building tools for analysing and understanding their performance. Including, but not limited to, prompt / context engineering.
- Experience collaborating in cross functional teams, working through ambiguity to deliver high quality results.
- Have 0 to 1 experience with a bias towards shipping and learning, while balancing a high-quality bar.
- Proven ability to collaborate and contribute to a positive, inclusive work environment, fostering knowledge sharing and growth within the team.
- Experience in healthcare technology, or experience in the health domain.
- Experience with data engineering - handling text dataset sourcing, curation, and processing tasks at scale.
- Passionate about conversational AI and its deployment.
- Demonstrated written and verbal communication skills with the ability to work closely with cross-functional teams, including product managers, designers, and other engineers.
- Passion for learning new technologies and staying up to date with industry trends, best practices, and emerging technologies and patterns in AI.
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