The RoleWe are seeking a highly motivated Senior Machine Learning Engineer / Data Scientist to join our AI/ML team. This individual will play a central role in designing and implementing advanced AI/ML systems with a focus on Retrieval-Augmented Generation (RAG), graph-based RAG, large language models (LLMs), agentic orchestration, and conversational AI (chatbot) solutions. Working closely with the Head of AI/ML and cross-functional partners, you will build and optimize LLM-powered pipelines and multi-agent systems that integrate knowledge graphs, multi-omics data, and biological context to uncover disease-driving proteins and pathways. The insights generated will directly support therapeutic discovery and development.
Key Responsibilities- Architect and implement scalable RAG and LLM-based systems that integrate multi-modal data sources, including knowledge graphs, documents, and structured biological datasets.
- Design and deploy RAG and graph-based RAG pipelines that leverage LLMs and knowledge graphs to retrieve, reason over, and synthesize complex biological information.
- Build and maintain agentic orchestration frameworks (multi-agent systems) that coordinate LLM-based agents for end-to-end scientific reasoning, data retrieval, and decision support.
- Collaborate with data engineering teams to design data pipelines that harmonize and prepare large-scale omics datasets for model training.
- Develop and optimize conversational AI (chatbot) interfaces that enable scientists and stakeholders to query, explore, and interact with internal data and model outputs using natural language.
- Partner with experimental scientists to ensure model outputs are biologically interpretable and experimentally testable.
- Stay abreast of advances in LLMs, RAG architectures, agentic AI, and conversational AI; bring innovative ideas into the team.
Qualifications- Ph.D. in Computer Science, Machine Learning, Applied Mathematics, Computational Biology, or related field with 1-3 years of industry experience (preferred); or M.S. in a related field with 4-6 years of industry experience.
- Proven track record in building LLM-based applications, with hands-on expertise in RAG, graph-based RAG, agentic orchestration, and/or chatbot development.
- Proficiency in Python and LLM/ML frameworks such as LangChain, Hugging Face Transformers, PyTorch, or similar.
- Experience working with multi-omics or high-dimensional biological data is a plus
- Familiarity with probabilistic modeling, causal reasoning, or statistical inference is a plus.
- Strong experience with knowledge graph technologies, graph databases, and vector databases.
- Demonstrated ability to work in cross-disciplinary teams, communicate complex ideas clearly, and deliver results in fast-moving environments.
Why Join Us?This role offers a unique opportunity to shape a next-generation AI/ML platform at the intersection of computation and drug discovery. You will work in a collaborative environment with leaders in biology, computation, and therapeutics - helping to expand the boundaries of the proteome and accelerate the development of new medicines for patients.
The salary range for this role is $96,000 - $214,500. Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. ProFound Therapeutics, Inc. currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on ProFound Therapeutics, Inc.'s good faith estimate as of the date of publication and may be modified in the future.
