Machine Learning Engineer
Team: R&D
Location: Cambridge
Commitment: Full-Time
Workplace Type: hybrid
Key responsibilities
- Build automated reasoning over large knowledge graphs and proprietary methods for efficient generation of experimentally testable therapeutic hypotheses
- Contribute to building, maintaining and improving our rare-disease knowledge graphs used to identify and reason over novel therapeutic hypotheses
- Develop agentic tools and workflows to enable our teams to unlock insight from proprietary data and large datasets
- Contribute and advocate for best engineering practices across our tech teams
What success will look like in 6 months
- You’ve built a strong understanding of Healx’s drug discovery workflows, our rare-disease knowledge graphs and the key users of our platform
- You’ve delivered at least one meaningful improvement to our knowledge graph reasoning or hypothesis-generation stack (from prototype through to production), with appropriate evaluation, testing and documentation
- You’re operating effectively in our hybrid, cross-functional environment—communicating progress and trade-offs clearly, partnering well with scientists and engineers, and demonstrating ownership from discovery through delivery
- You’re consistently applying and advocating for strong engineering practices (e.g., code quality, reviews, reproducibility, experiment tracking, monitoring/observability where relevant), helping raise the bar across the team
What we're looking for
- You have 2-5 years professional (in academia or industry) experience in machine learning, artificial intelligence or related field
- You are excited about taking on new challenges and responsibilities in a mission-driven startup aiming at improving patient outcomes
- You have an advanced degree (masters, PhD) in machine learning, biochemistry or related field with a focus on applied research or equivalent industry experience applying machine learning to complex real-world problems
- You have a strong software development experience in Python and a good appreciation of the principles of software engineering
- You thrive in a highly cross-functional environment and you appreciate the opportunity to step up and leave your mark by taking ownership of meaningful technical challenges, contributing ideas that shape the direction of our platform and driving solutions from concept through to deployment
- You are able to work independently to scope, plan and deliver end-to-end machine learning solutions, managing your own priorities effectively and communicating progress and blockers proactively
- You are comfortable navigating a degree of ambiguity, making pragmatic decisions when needed, and you know when to seek input from the broader team to ensure quality and alignment
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