Associate Director: Machine Learning (Drug Discovery)

Location: Boston, MA (Hybrid or Remote - U.S. Based)
Employment Type: Full-time | Permanent

About the Opportunity

iO are seeking an Associate Director for one of our leading customers to lead the implementation of advanced machine learning strategies across its therapeutic discovery programs. This is a highly technical and hands-on role, focused on building production-grade AI/ML systems to accelerate the identification of novel drug targets and optimize therapeutic development pipelines.

You will collaborate across computational biology, chemistry, and data science teams to bring innovative ML solutions into real-world workflows, helping to advance treatments across a range of complex disease areas.

Responsibilities

Design and deploy advanced ML models (e.g., GNNs, transformers, reinforcement learning, diffusion models) for target discovery and lead optimization
Integrate multi-modal biological, chemical, and clinical datasets into predictive platforms
Develop agent-based systems to enhance scientific reasoning, hypothesis generation, and in silico experimentation
Contribute to building foundational AI infrastructure, including knowledge graphs and multi-agent environments
Translate research models into production-level tools used across drug discovery programs
Collaborate cross-functionally with domain experts in biology, pharmacology, and chemistry
Mentor junior ML scientists and contribute to strategic planning across computational R&D

Experience

PhD (or MS with equivalent experience) in Machine Learning, AI, Computational Biology, Bioinformatics, or a related field
8+ years of experience designing and deploying ML systems in a life sciences context
Strong coding ability in Python and experience with frameworks such as PyTorch or TensorFlow
Background in small molecule or biologics drug discovery, especially across oncology, neuroscience, or immunology
Experience with large-scale data integration, systems biology, and model interpretability
Familiarity with cloud-based ML pipelines (AWS, Azure, or GCP) and production-level engineering practices
Entrepreneurial mindset with the ability to work autonomously in fast-paced, collaborative environments

Preferred

Agentic or reasoning AI systems
Active learning or generative models in drug design
Multi-scale modeling and real-world evidence integration
Prior experience in early-stage biotech or therapeutic R&D platforms

Please get in touch if you are interested e.hincks @ioassociates.com

Unfortunately sponsorship cannot be provided for this position