ProFound Therapeutics is pioneering the discovery of the expanded human proteome to unlock a new universe of potential therapeutics. By integrating multi-omics, advanced computation, and translational biology, we aim to reveal and characterize thousands of previously uncharted proteins and systematically explore their role in health and disease.
Requirements
- Proven track record in machine learning model development, with expertise in transformers, graph neural networks, generative modeling, or causal inference.
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, JAX, or PyTorch Geometric.
- Experience working with multi-omics or high-dimensional biological data is strongly preferred.
- Strong background in probabilistic modeling, causal reasoning, or statistical inference.
- Familiarity with knowledge graph technologies and graph databases is a plus.
Responsibilities
- Architect and implement scalable ML systems that integrate multi-modal data (genomics, transcriptomics, proteomics, imaging, perturbation data).
- Develop and deploy graph-based, transformer-based, and generative models (including LLMs) to capture biological relationships and simulate interventions.
- Contribute to building a multi-agent causal AI framework that integrates causal graph learning, intervention simulation, and knowledge graph reasoning.
- Collaborate with data engineering teams to design data pipelines that harmonize and prepare large-scale omics datasets for model training.
- Implement, evaluate, and optimize causal inference methods (e.g., DAG learning, treatment-effect estimation, counterfactual modeling).
- Partner with experimental scientists to ensure model outputs are biologically interpretable and experimentally testable.
- Stay abreast of advances in ML/AI, causal modeling, and computational biology; bring innovative ideas into the team.
Other
- Highly motivated Senior Machine Learning Engineer / Data Scientist to join our AI/ML team.
- Working closely with the Head of AI/ML and cross-functional partners.
- Demonstrated ability to work in cross-disciplinary teams, communicate complex ideas clearly, and deliver results in fast-moving environments.
- Seeking individuals with an entrepreneurial spirit, strong communication skills, and comfort working in and contributing to a dynamic and cross-functional team environment.
- The level of the role will be commensurate with the education and years of experience of the identified candidate.
