Senior Machine Learning Engineer/Data Scientist

Responsibilities

• Architect and implement scalable RAG and LLM-based systems integrating multi-modal data sources, including knowledge graphs and structured biological datasets.
• Design and deploy graph-based RAG pipelines to retrieve, reason over, and synthesize complex biological information.
• Build and maintain agentic orchestration frameworks (multi-agent systems) for scientific reasoning and decision support.
• Collaborate with data engineering teams to design pipelines that harmonize large-scale omics datasets for model training.
• Develop conversational AI interfaces to enable scientists to interact with internal data using natural language.
• Partner with experimental scientists to ensure model outputs are biologically interpretable and testable.

Requirements

• Ph.D. in Computer Science, Machine Learning, Applied Mathematics, Computational Biology, or a related field with 1–3 years of industry experience; or an M.S. in a related field with 4–6 years of industry experience.
• Proven track record in building LLM-based applications with expertise in RAG, graph-based RAG, and agentic orchestration.
• Proficiency in Python and ML/LLM frameworks such as LangChain, Hugging Face Transformers, or PyTorch.
• Strong experience with knowledge graph technologies, graph databases, and vector databases.
• Ability to work in cross-disciplinary teams and communicate complex technical ideas clearly.

Preferred Qualifications

• Experience working with multi-omics or high-dimensional biological data.
• Familiarity with probabilistic modeling, causal reasoning, or statistical inference.

Benefits

• Healthcare coverage.
• Annual incentive program.
• Retirement benefits.
• A collaborative environment working at the intersection of computation and drug discovery.

About the Company

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.