Senior Full-Stack Software Engineer - LLM & Generative AI

We're seeking an experienced Full-Stack Software Engineer to join our team in Montreal. Together, we'll build products and services for two main audiences: internally, for our fellow scientists and researchers, and externally, to support Valence's open science and community initiatives. We're looking for someone who is flexible, versatile, and can wear several hats when the need arises. Our teams are small and cross-functional, offering abundant learning opportunities and the opportunity to build solutions for some of the world's most complex scientific problems.

More specifically, in this role, you will:

• Own full features of the projects you work on, building them across the full-stack of frontend to backend.


• Explore and implement reasoning systems using the LangChain ecosystem.


• Develop memory modules and ETL pipelines for up-to-date, production-ready databases.


• Build vector databases for Retrieval-Augmented Generation (RAG) applications, and traditional SQL databases interfacing with tools such as CDD Vault.


• Build evaluation systems for LLM agents, and establish observability and traceability for LLM autonomous systems.


• Write, deploy, and leverage Cloud-based infrastructure, third-party Software as a Service providers, and open-source libraries to deliver better features for our users.


• Be exposed to, and participate in, cutting-edge research and projects, at the intersection of Software Engineering, Machine Learning and Drug Discovery.


• See the impact of your work on end users and have your voice heard in the direction of your projects.
  
  Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.


• Solid, demonstrated experience in full-stack software engineering, including modern frontend (TypeScript, Next.js/React, and their associated ecosystem) and backend (Python, FastAPI/Django, and their ecosystem) development.


• Some experience with Cloud-based infrastructure (GCP, Vercel, etc).


• Demonstrated experience in building Software as a Service products, Web services APIs, and thinking in terms of platforms.


• A continuing ability and desire to own and deliver full-stack features, while always keeping the user in mind.


• A keen interest in bridging the gap between machine learning research and its practical application in production environments.


• Deep interest in building LLM-based agents and applications, ideally with some experience with LangChain or related libraries.


Nice to have:

• Some knowledge or experience in distributed system observability, especially OpenTelemetry, and associated tools like Honeycomb.


• Some knowledge or experience of Infrastructure as Code (Terraform), to manage Cloud-based infrastructure.


• Knowledge or desire to learn the necessary biology, chemistry, and physics knowledge to collaborate with an interdisciplinary team of drug discovery scientists, and bridge the gap with the engineering team.


Valence Labs is committed to creating a diverse and inclusive environment, where understanding and accommodating personal needs and preferences is a priority. Join our multidisciplinary team of passionate researchers, eager to push the boundaries of ML research and contribute to industrializing scientific discovery to radically improve lives.

Valence Labs is an AI research and productization engine within Recursion dedicated to industrializing scientific discovery to radically improve lives. Combining the intellectual freedom of academia with the resources and stability of industry, our focus is the development of highly-autonomous systems that will spearhead a fundamental shift in the way treatments are discovered and developed for complex disease. Our research is driven by optimism, purpose, and a shared vision for a healthier tomorrow. We publish in top journals and conferences, are deeply committed to open-science and open-source, and maintain some of the largest and most active research communities in our industry. Our team is located in London and Montreal, where we share close connections with Mila, the world's largest deep learning research institute.