Hexion

Applied ML Scientist - Active Learning

Hexion • $100K — $130K *
Columbus, OH 43230In-Person
Pharmaceuticals & Biotech
5 - 7 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Data Science, Statistics, Operations Research, or related field with substantial ML or optimization experience in chemistry or manufacturing.
  • 7+ years of relevant experience.
  • Expertise in Bayesian optimization and Gaussian processes, particularly in complex settings.
  • Hands-on experience designing and executing experimental campaigns or closed-loop optimizations.
  • Knowledgeable in applied statistics and uncertainty quantification techniques.
  • Strong Python programming skills with familiarity in ML and Bayesian optimization libraries.
  • Proficient in AI-assisted coding and emerging ML methods.

Responsibilities

  • Lead design and execution of optimization campaigns in chemistry and process development.
  • Collaborate with R&D and manufacturing to define optimization challenges.
  • Coordinate sequential experiment campaigns using advanced optimization techniques.
  • Select and maintain surrogate models to optimize decision-making and explore uncertainties.
  • Drive closed-loop optimization linking models to experimentation with actionable insights.
  • Partner with engineers to deploy and oversee optimization systems.
  • Explore and integrate cutting-edge ML methods to enhance optimization processes.
  • Clearly communicate methods and limitations to both technical and non-technical teams.

Benefits

  • Opportunity to work at the intersection of machine learning and chemical processes.
  • Engagement with cross-disciplinary teams, enhancing collaboration skills.
  • Access to advanced optimization tools and technologies.
  • Potential for professional growth through exposure to emerging ML methods and innovations in optimization.
Full Job Description
Job Responsibilities

  • Lead the design and execution of optimization and active-learning campaigns across chemistry, formulation, and process development.
  • Collaborate with R&D and manufacturing on framing optimization problems with design spaces, decision variables, objectives, and hard and soft constraints.
  • Design and coordinate sequential experiment campaigns using Bayesian optimization and active learning, accounting for operational variabilities and constraints.
  • Select and maintain surrogate models for acquisition, using model uncertainty to drive the search and respecting each model's domain of validity.
  • Drive closed-loop optimization that connects surrogate models to experimentation, with emphasis on decision quality, exploration versus exploitation, and actionable recommendations.
  • Partner with ML engineers, software engineers, and process engineers to deploy and monitor optimization systems.
  • Explore and adopt emerging ML methods, including LLM and agentic approaches, to advance optimization.
  • Communicate methods, results, and their limitations clearly to technical and non-technical audiences.


Minimum Qualifications

  • Bachelor's degree in Computer Science, Data Science, Statistics, Operations Research, or a related field, with substantial relevant experience in ML modeling or optimization experience for chemistry, formulation, process, or manufacturing problems.
  • 7+ years experience.
  • Demonstrated expertise in Bayesian optimization and Gaussian processes, including kernels, acquisition functions, and batch, multi-objective, and constrained settings.
  • Experience designing and running experiment campaigns or closed-loop optimization.
  • Experience in applied statistics and uncertainty quantification, with emphasis on calibrated posteriors that drive acquisition.
  • Strong Python skills and experience with mainstream Python-based ML and Bayesian optimization 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.


Preferred Qualifications

  • Master's degree in Computer Science, Data Science, Statistics, Operations Research, or a related field.
  • Experience with active learning and physics-informed approaches for optimization in chemical synthesis, formulation, or process development.
  • Experience working with manufacturing, process, quality, or plant data, including issues such as batch-to-batch variability, raw-material variability, model drift, and changing operating conditions.
  • Familiar with ML engineering core tasks and techniques, such as data and optimization pipelines, model deployment, and MLOps.
  • Knowledge of chemistry ML core areas such as cheminformatics, molecular representation, predictive modeling, and chemistry foundation models.

About Hexion

Hexion is a global specialty chemicals company that produces a range of resins, adhesives, and other chemical products. The company's products are used in a variety of industries, including automotive, construction, and electronics. Hexion was formed in 2005 through the merger of two chemical companies, Borden Chemical and Resolution Performance Products. The company is headquartered in Columbus, Ohio and has operations in North America, Europe, and Asia.
Learn more about Hexion
Size
4,300 employees
Industry
Manufacturing & Automotive
Founded
1857
* Ladders Estimates

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