Hybrid Senior Research Scientist – Large Language Models for Genomics

at Deep Genomics

• Job title: Senior Research Scientist – Large Language Models for Genomics
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: AWS, Cloud, Google Cloud Platform, Python
• Location requirements: Hybrid, Toronto, Canada

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.

Requirements

• 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.

Benefits

• 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.