Materials AI/ML Specialist (AI)

Location: On-site in Maplewood, Minnesota, United States; at least four days per week at the hirify.global Center. Up to 5% domestic travel may be required. Relocation assistance may be authorized.

Salary: $145,676–$178,049 annually, including base pay and variable incentive pay if eligible.

Company

hirify.global develops creative products and technologies across materials, manufacturing, and other industrial applications.

What you will do

• Apply AI/ML methods, including Bayesian optimization, cheminformatics, active learning, and AI hypothesis generation, to plan experiments for liquid adhesive and PSA/tape formulations.
• Conduct hands-on formulation, mechanical, and performance testing, including overlap shear, DMA, and handling-strength tests.
• Analyze formulation, process, and performance data using statistical and machine learning approaches.
• Develop and use digital tools for experiment planning, data analysis, and knowledge capture.
• Apply generative AI and LLM-assisted literature mining to product development challenges.
• Communicate technical findings to chemists, engineers, business leaders, and other cross-functional stakeholders while managing multiple R&D programs.

Requirements

• Bachelor’s degree in Chemistry, Materials Science, Chemical Engineering, or a related field.
• At least three years of experience in new product development, formulation, or experimental/lab work.
• At least two years of experience using AI/ML or data science tools in experimental or laboratory work.
• Working knowledge of Python and common machine learning or data science libraries.
• Ability to work independently, learn new formulation and testing protocols, and follow laboratory safety requirements.
• Must be legally authorized to work in the United States without employment visa sponsorship.

Nice to have

• Master’s degree or higher in a relevant field.
• Five or more years of hands-on product development or formulation experience.
• Experience with adhesive, PSA, tape, coating, or polymer formulation and mechanical testing.
• Experience with Bayesian optimization, active learning, surrogate modeling, or sequential design of experiments.
• Experience using LLMs or generative AI for materials discovery, hypothesis generation, or literature mining.

Culture & Benefits

• Collaboration with cross-functional teams in a global R&D environment.
• Medical, dental, and vision benefits.
• Health savings and flexible spending accounts.
• Disability, life insurance, paid absence, retirement, and voluntary benefits.
• Safety is a core value, with expectations to follow EHS policies, identify hazards, and support continuous improvement.