Stealth Biotech | Melbourne, Australia
A venture-backed biotechnology company based in Melbourne is seeking a Director of Machine Learning to lead and scale its AI-driven drug discovery platform. The company is advancing a novel therapeutic pipeline targeting high-unmet-need diseases and is building an integrated computational–experimental engine to accelerate target identification, molecule design, and translational decision-making.
This is a senior, hands-on leadership role for an individual with deep biotech domain expertise and a demonstrated track record applying machine learning to real-world drug discovery challenges.
The Opportunity You will define and execute the machine learning strategy across the discovery lifecycle — from target identification and validation through to lead optimisation and candidate nomination. Working closely with biology, chemistry and translational teams, you will build models that materially impact pipeline progression and reduce experimental cycle times.
This role sits at the intersection of computational science and therapeutic development, requiring both strategic oversight and the ability to operate deeply at a technical level.
Key Responsibilities
- Develop and lead the company’s machine learning strategy aligned to therapeutic and platform objectives
- Design, implement and deploy ML models across target discovery, multi-omics integration, molecular design and optimisation
- Partner cross-functionally with wet-lab biology, medicinal chemistry and translational teams to integrate computational outputs into experimental workflows
- Build and mentor a high-performing computational biology / ML team
- Establish robust data engineering, MLOps and reproducibility standards
- Translate complex modelling outputs into actionable insights for executive and scientific stakeholders
- Contribute to investor discussions and technical diligence as required
- PhD (or equivalent experience) in Machine Learning, Computational Biology, Bioinformatics, Computer Science, Physics, Applied Mathematics or related field
- 8+ years of industry experience within biotech or pharma, with direct exposure to drug discovery environments
- Demonstrated experience building and deploying ML models in therapeutic discovery (e.g., target identification, biomarker discovery, generative chemistry, structure-based modelling, multimodal data integration)
- Strong understanding of biological data types (genomics, transcriptomics, proteomics, single-cell, imaging, clinical datasets)
- Proven track record of influencing or advancing drug discovery programs through computational approaches
- Experience managing and scaling technical teams
- Experience working within CNS, oncology, rare disease or other high-unmet-need therapeutic areas
- Familiarity with generative models for molecule design (e.g., diffusion models, graph neural networks, transformer-based architectures)
- Experience integrating experimental feedback loops into ML pipelines
- Prior exposure to early-stage, venture-backed environments
- Python (PyTorch / TensorFlow / JAX)
- ML Ops frameworks and scalable cloud infrastructure (AWS / GCP / Azure)
- Experience working with structured and unstructured biological datasets
- Strong software engineering discipline and reproducibility standards
- Opportunity to architect and own a core AI-driven discovery engine from an early stage
- Direct impact on therapeutic programs addressing serious disease
- Competitive compensation package including equity participation
- Melbourne-based leadership role within a well-funded, growth-stage biotech
Confidential enquiries can be made directly.
