About the role

Senior Research Scientist specializing in large language models for genomics at Deep Genomics. Join us in revolutionizing drug discovery using AI and innovative therapeutic design.

Responsibilities

Design and implement multi-agent workflows that integrate internal foundation models (e.g., BigRNA, REPRESS, FlashRNA) and external tools to identify new biological hypotheses.
Develop systems that leverage Retrieval Augmented Generation (RAG) by connecting LLMs to internal scientific documents, SOPs, and structured biological databases.
Collaborate with the machine learning team on model distillation strategies to create smaller, faster models suitable for a real-time, interactive chat interface.
Build out and maintain the infrastructure for the LLM agent, including databases and model context protocol (MCP) endpoints.
Work closely with end-users in therapeutic design, target discovery, and experimental biology to identify key use cases, gather feedback, and rapidly iterate on the product.
Ensure the system is transparent and trustworthy by building "explainable AI" features that help users understand and verify the AI's outputs and decisions.

MSc or PhD in Computer Science, Computational Biology, Bioinformatics, or a related field.
3+ years of hands-on experience architecting and building complex applications using Large Language Models.
Expert knowledge of Python and modern MLOps frameworks and tools; experience with agentic frameworks like LangChain is essential.
Demonstrated experience in building multi-agent systems that can plan, execute tasks, and interact with external tools and APIs.
Familiarity with high-performance computing environments and cloud services (e.g., AWS, GCP).
Excellent communication skills and the ability to work effectively in a multidisciplinary team, translating the needs of biologists and drug developers into technical solutions.
Intellectual curiosity, critical thinking, and a commitment to innovation and scientific rigor.

A collaborative and innovative environment at the frontier of computational biology, machine learning, and drug discovery.
Highly competitive compensation, including meaningful stock ownership.
Comprehensive benefits - including health, vision, and dental coverage for employees and families, employee and family assistance program.
Flexible work environment - including flexible hours, extended long weekends, holiday shutdown, unlimited personal days.
Maternity and parental leave top-up coverage, as well as new parent paid time off.
Focus on learning and growth for all employees - learning and development budget & lunch and learns.
Facilities located in the heart of Toronto - the epicenter of machine learning and AI research and development, and in Kendall Square, Cambridge, Mass. - a global center of biotechnology and life sciences.