Machine Learning Engineer
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Location
Boston
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Sector:
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Job type:
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Salary:
Negotiable
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Contact:
Edward Hincks
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Contact email:
e.hincks@ioassociates.com
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Job ref:
BBBH160984_1748442893
Machine Learning Engineer - Founding Team Opportunity
Location: Boston with hybrid options available
Type: Full-time | Early-stage | Equity + Salary
About the Company
iO Associates are working with a stealth startup operating at the convergence of AI, biology, and data science. The company is rethinking how new therapies are developed by combining modern machine learning with advanced experimental and real-world data. This approach enables predictive insights into how potential treatments might behave - long before clinical testing.
This is a rare opportunity to join as one of the first ML hires and help architect a next-gen platform for therapeutic discovery.
What You'll Do
Design and implement machine learning models (e.g., GNNs, Transformers, diffusion models) for complex biological and chemical prediction tasks
Work across diverse datasets, from genomic to molecular to clinical, to power data-driven decision-making
Collaborate closely with cross-functional experts across computational and life sciences
Contribute to building scalable ML infrastructure for ongoing iteration and platform growth
What We're Looking For
Graduate degree (MS/PhD) in Computer Science, Computational Biology, Bioinformatics, or a related field
Hands-on experience applying ML to scientific or structured data problems (e.g., PyTorch, RDKit, Hugging Face, etc.)
Interest or background in biology-adjacent domains such as pharmacology, systems biology, or cheminformatics
Proactive, startup-ready mindset and excitement for working in a fast-moving, high-impact environment
Bonus Skills
Experience with PK/PD modeling, multi-modal integration, or real-world evidence
Exposure to generative models, active learning, or reinforcement learning
Familiarity with cloud-native ML workflows and infrastructure
Why Join
Join a mission-driven company with ambitious scientific and technical goals
Help shape foundational tools and platforms from day one
Work alongside top-tier collaborators across multiple disciplines
Competitive compensation with meaningful equity and remote flexibility
If you are interested in applying, please click the link below or get in touch with Ed @ iO.
Unfortunately sponsorship cannot be provided
