3M · 3 hours ago
AI Experimental Systems Research Scientist (Causal Learning & Adaptive Experimentation)
3M is a diverse and innovative company that supports its employees' growth and collaboration. They are seeking an AI Experimental Systems Research Scientist to develop foundational methods for adaptive learning systems that reason and experiment in complex environments, focusing on causal learning and statistical inference.
AutomotiveCleaning ProductsConsultingElectronicsEnterprise SoftwareManufacturing
Responsibilities
Designing and implementing adaptive experimental systems that operate continuously under nonstationarity, interference, and delayed or indirect outcomes
Developing causal estimands, randomization schemes, and inference procedures whose primary goal is identifiability and validity, not just reward optimization
Embedding rigorous experimental control directly into learning systems, including experimentation on the system’s own learning mechanisms, parameters, and representational choices
Translating principles from experimental design, causal inference, and sequential decision-making into robust, always-on system behavior
Working from whiteboards, research discussions, and evolving specifications—not fixed product requirements or static datasets
Implementing and maintaining research code that supports hierarchical experimentation, baseline control streams, and statistically valid online inference
Creating diagnostics, monitoring tools, and guardrails to ensure learning systems remain calibrated and do not stabilize spurious structure over time
Collaborating with interdisciplinary researchers to stress-test experimental learning mechanisms under realistic, adversarial conditions
Qualification
Required
Ph.D. in Statistics, Biostatistics, Economics, Computer Science, Data Science, Operations Research, or a closely related field (completed and verified prior to start)
Deep grounding in experimental design and statistical inference, including randomized experiments and causal estimands
Demonstrated ability to implement research-grade statistical or experimental methods in a general-purpose programming language (e.g., Python)
Experience working in research settings where the problem definition evolves and correctness takes precedence over convenience
Preferred
Experience with adaptive or sequential experimentation (e.g., response-adaptive trials, causal bandits, best-arm identification)
Familiarity with causal inference frameworks spanning both design-based and model-based approaches
Strong intuition for identifiability, bias–variance tradeoffs, and statistical validity in complex, real-world settings
Experience working with nonstationary systems, concept drift, or delayed feedback loops
Experience reasoning about interference, carryover effects, time-varying treatments, or non-independent experimental units
Comfort designing experiments where the learning process itself is the object under experimental control
Familiarity with hierarchical or clustered experimental designs and multi-level inference
Interest in foundational questions about how autonomous systems should reason, experiment, and adapt in the world
Ability to communicate complex statistical ideas clearly to interdisciplinary collaborators
Curiosity, intellectual humility, and a strong preference for epistemic correctness over short-term performance gains
Benefits
Medical
Dental & Vision
Health Savings Accounts
Health Care & Dependent Care Flexible Spending Accounts
Disability Benefits
Life Insurance
Voluntary Benefits
Paid Absences
Retirement Benefits
Company
3M
3M is a global company that applies science to life, offering products and solutions across various industries.
H1B Sponsorship
3M has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (17)
2024 (23)
2023 (27)
2022 (54)
2021 (36)
2020 (31)
Funding
Current Stage
Public CompanyTotal Funding
$5MKey Investors
US Department of Energy
2024-03-13Grant· $5M
1978-01-13IPO
Leadership Team
Recent News
Sherwood News
2026-01-22
GlobeNewswire
2026-01-05
Company data provided by crunchbase