Applied ML Scientist - Chemistry
Hexion
Company Overview Imagine Everything. Build the Future with Hexion. At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress-developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future. This is where bold thinkers, problem-solvers, and innovators come together to shape what's next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward. We don't follow the status quo-we challenge it, disrupt it, and improve it. Every role at Hexion is part of something bigger. We invest in innovation, sustainability, and continuous development-equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide. Your Future Starts Here. If you're ready to push limits, reimagine what's possible, and create the extraordinary, Hexion is where you belong.
Anything is possible when you imagine everything. Job Responsibilities
Anything is possible when you imagine everything. Job Responsibilities
- Lead ML model development for prediction and optimization across chemistry, formulation, property, and process.
- Collaborate with R&D and manufacturing on problem framing and translate business goals into well-posed multi-objective optimization modeling tasks.
- Curate and analyze chemical and experimental data, assessing quality and structure and the limits it places on modeling.
- Develop and select input representations for raw materials, chemistry, and signal data, such as molecular descriptors and fingerprints, learned embeddings, and spectral features.
- Select, train, and evaluate models across families such as regression, tree ensembles, Gaussian processes, neural networks including physics-informed architectures, and chemistry foundation models.
- Quantify and calibrate model performance and uncertainty, and define each model's domain of validity for downstream use.
- Apply transfer learning to make use of multiple data sources, such as related tasks, prior campaigns, and data of varying fidelity and completeness.
- Explore and adopt emerging ML methods, including LLM and agentic approaches, to advance modeling.
- Communicate methods, results, and their limitations clearly to technical and non-technical audiences.
- Bachelor's degree in Computer Science, Data Science, Computational Chemistry, Cheminformatics, or a related field, with substantial relevant experience in ML modeling experience for chemistry, formulation, process, or manufacturing problems.
- Domain knowledge in chemistry, preferably polymer chemistry.
- Demonstrated ability to develop molecular and materials representations and to select, train, and evaluate predictive models across families.
- Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity.
- Strong Python skills and experience with mainstream Python-based ML frameworks and tools.
- Active use of AI-assisted coding and other AI tools in daily work, with familiarity with emerging ML methods including LLM and agentic approaches.
- Strong communication, collaboration, and stakeholder management skills for working with R&D, manufacturing, and business teams.
- Master's degree in Computer Science, Data Science, Computational Chemistry, Cheminformatics, or a related field.
- 5+ years experience.
- Experience with cheminformatics, chemistry foundation models and physics-informed modeling.
- Familiarity with active learning, Bayesian optimization, and related techniques.
- Knowledge of ML engineering core tasks and techniques, such as data and optimization pipelines, model deployment, and MLOps.
Vacancy posted 18 hours ago
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