Jobs / United States / 3M Company
Materials AI/ML Specialist
3M Company · 🇺🇸 US, Minnesota, Maplewood
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 17 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 6 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What 3M Company paid sponsored hires in similar roles7 certified filings for “Senior Research Engineer” (Materials Engineers) in MN: $117k–$131k, median $128k. Most were filed at wage level II (43%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Last confirmed live 2 days agoWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — 3M Company
The US Department of Labor certified 17 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 6 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for 3M Company →
About the role
Job Description: Materials AI/ML Specialist Collaborate with Innovative 3Mers Around the World Choosing where to start and grow your career has a major impact on your professional and personal life, so it’s equally important you know that the company that you choose to work at, and its leaders, will support and guide you. With a wide variety of people, global locations, technologies and products, 3M is a place where you can collaborate with other curious, creative 3Mers. This position provides an opportunity to transition from other private, public, government or military experience to a 3M career. The Impact You’ll Make in this Role As a Materials AI/ML Specialist, you will apply artificial intelligence and machine learning techniques to accelerate new product development in formulation science. Partnering closely with product developers, you will help modernize how experiments are planned, run, and analyzed - bringing data-driven speed to lab-based innovation. Here, you will make an impact by: • Applying AI/ML methods (e.g., Bayesian optimization, cheminformatics, active learning, AI hypothesis generation ) to guide and accelerate experimental planning for new liquid adhesive and pressure-sensitive adhesive (PSA)/tape formulations • Running hands-on formulation, mechanical, and performance testing (e.g., overlap shear, DMA, handling strength) to generate high-quality data for AI/ML-driven analysis • Analyzing formulation, process, and performance data using statistical and machine learning approaches to extract insights that drive faster, better technical decisions • Continuously expanding your AI/ML capabilities - including techniques such as Bayesian optimization and generative AI/LLM-assisted literature mining - and applying them to live product development challenges • Using and helping evolve shared digital tools and platforms for experiment planning, data analysis, and knowledge capture • Sharing insights and learnings across programs to strengthen data-driven development practices more broadly • Communicating technical findings clearly to cross-functional stakeholders, including chemists, engineers, and business leaders • Balancing lab time and analytical work across multiple concurrent development programs • Operating with a high degree of independence in a fast-paced R&D environment, quickly picking up new formulation, testing, and lab safety protocols as needed Your Skills and Expertise To set you up for success in this role from day one, 3M requires (at a minimum) the following qualifications: • Bachelor's degree in Chemistry, Materials Science, Chemical Engineering, or a related field (completed and verified prior to start) • Three (3) years of experience in new product development, formulation, or experimental/lab work, in an academic, private, public, government, or military environment • Two (2) experience using AI/ML or data science tools within your own experimental/lab work (e.g., machine learning, AI hypothesis generation, design of experiments software, statistical modeling, data analysis tools) , with a demonstrated desire and aptitude to expand this skill set Additional qualifications that could help you succeed even further in this role include: • Master's degree or higher in Chemistry, Materials Science, Chemical Engineering, or a related field • Five (5) or more years of hands-on new product development or formulation experience • Hands-on experience with adhesive, PSA, tape, coating, or polymer formulation and mechanical testing (e.g., overlap shear, DMA, handling strength) • Familiarity with Bayesian optimization, active learning, surrogate modeling, or other sequential/statistical design-of-experiments techniques • Exposure to large language models (LLMs) or generative AI tool