ABOUT US

At UCM, we use AI to design smarter, safer, and more sustainable molecules for everyday life. Our mission is to merge advanced generative models with chemistry to create high-performance, sustainable ingredients and materials. Backed by recent investment and deep industry expertise, we’re assembling a passionate team to redefine molecular design—from food tech to personal wellness.

REQUIRED QUALIFICATIONS

• Education: M.Sc. (Ph.D. preferred) in Chemistry, Computer Science, Chemical Engineering, Pharmaceutical Sciences, or a related field.
• Experience: Hands-on experience with cheminformatics and machine learning applied to chemical data—either through academic research or industry projects.
• Programming: Strong Python skills and fluency with libraries such as RDKit, scikit-learn, pandas, and NumPy. Visualization tools (e.g., seaborn, Matplotlib) and machine learning frameworks (e.g., PyTorch, TensorFlow).
• Generative Models: Working knowledge and implementation experience with at least one generative model type (GAN, VAE, or diffusion models).
• Chemical Representations: Familiarity with SMILES, InChI, SELFIES, molecular graphs, and structure-based descriptors.
• Collaboration: Excellent communication skills and experience working in interdisciplinary teams.
• Mindset: Curiosity, adaptability, and a desire to work in a fast-paced, startup environment where creativity is valued.

DESIRABLE EXPERIENCE

• Deep knowledge of cheminformatics workflows (QSAR, clustering, hit finding, similarity scoring).
• Experience with advanced generative architectures (e.g., flow models, autoregressive models, graph-based diffusion).
• Background in computational chemistry, docking, molecular dynamics, or DFT.
• A track record of conference presentations or peer-reviewed publications.
• Previous experience in a startup or early-stage R&D setting.

THE ROLE

We are looking for a Machine Learning Scientist with expertise in generative modeling and a background in cheminformatics or computational chemistry. You’ll be at the core of our molecule design engine—building models that propose novel structures and collaborating with chemists and market experts to translate those models into real-world impact.
This is a full-time hybrid role based in Vancouver, with flexible remote work options. Compensation includes a base salary in the $50K–$85K CAD range (commensurate with experience) plus stock options.

KEY RESPONSIBILITIES

• Data Preparation & Featurization: Aggregate, curate, and prepare large chemical datasets. Design and apply molecular featurization strategies (e.g., SMILES, graph representations, fingerprints).
• Predictive Modeling: Apply machine learning models to property prediction to inform molecular design.
• Generative Modeling: Build and evaluate generative models (e.g., GANs, VAEs, diffusion models) for de novo molecular generation.
• Experimental Collaboration: Work closely with chemists and product teams to validate model-generated compounds and incorporate experimental feedback into model refinement.
• Innovation & Research: Stay on top of developments in AI for molecular design. Propose and prototype new methods to improve our platform.
• Communication: Present results clearly to a cross-functional team. Contribute to internal reports, publications, and patent applications when relevant.