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# Machine Learning Scientist - Generative Molecular Design

- **Company:** SB Technology, Inc.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $134,000.0 - $252,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Oracle (Applications), Tensorflow, Software Construction, Reinforcement Learning, Data Processing, Google Cloud, Cloud Platform System, Data Ingestion, Pytorch, Large Language Models, Information Technology
- **Published:** October 27, 2026
- **Apply:** https://www.builtincolorado.com/job/machine-learning-scientist-generative-molecular-design/11893809?handler=ApplyRedirect

## About the Role

* Hands-on expertise building and shipping modern generative or applied ML for material discovery with at least 4+ years of experience delivering these solutions in industry or an equivalent research setting.
 * Demonstrated ability to write clean, maintainable, and robust production-grade code designed for industry-scale applications.
 * Proven ability to build scalable ML, e.g. using PyTorch, TensorFlow, or JAX.
 * Familiarity with cloud-based platforms (e.g. Google Cloud Platform, AWS) for compute and data processing and storage.
 * PhD or MSc in Computational Chemistry, Physics, Computer Science, or equivalent.
 * Excellent communication skills and a record of fostering successful internal collaboration in a fast-paced environment.
 * Experience developing ML code in a collaborative environment using modern software engineering best practices.

## Description

* Architect and evolve our flagship generative platform, serving as a core contributor to the engine that will redefine how the industry discovers new materials.
 * Implement and optimize state-of-the-art generative models - including diffusion, flow-matching, and GFlowNets, or LLM- and agent-based methods - to navigate high-dimensional chemical space and solve the multi-objective optimization problems that material discovery presents.
 * Own the reward interface. Integrate learned surrogates, and simulation-derived oracles as the objective signal driving generation, and design reward formulations that hold up when several objectives are in genuine tension e.g. performance against environmental and safety constraints.
 * Develop and deploy computational methods and workflows to generate and evaluate hypotheses, guiding design decisions and influencing project direction.
 * Identify relevant data sources and take responsibility for data ingestion, QC, and validation.
 * Collaborate daily with a core group of ML researchers to implement frontier generative architectures, while working closely with the broader R&D, discovery, engineering, and product teams.