AI/Machine Learning Engineer

3M•Maplewood, MN

2d•$124,127 - $151,710•Onsite

About The Position

This position provides an opportunity to transition from other private, public, government or military experience to a 3M career. As an AI Software Developer, Early Career, you will join an internal incubator building a new-to-the-world AI architecture and a new technical category. You will work alongside experienced researchers and engineers to convert Python research and development code into scalable production components, primarily in Rust. You will receive clearly scoped assignments and learn an uncommon approach to AI while building tests, simulations, runtime services, and performance improvements that help move foundational research into real-world systems.

Requirements

Bachelor's degree or higher in computer science, computer engineering, electrical engineering, applied mathematics, physics, cognitive science, computational neuroscience, or a related field (completed and verified prior to start) from an accredited institution.
OR High School Diploma/GED (completed and verified prior to start) AND five or more years of experience developing, testing, and maintaining, software or technology systems, including substantial hands-on programming experience.
Five (5) years programming ability in Python and either C++, Rust, or another systems programming language.
Three (3) years of core software-engineering practices, including version control, code review, debugging, automated testing, and technical documentation.
Must be legally authorized to work in country of employment without sponsorship for employment visa status (e.g., H1B status).

Nice To Haves

Ability to understand unfamiliar algorithms, break work into testable components, and collaborate effectively with researchers and senior engineers.
Hands-on Rust experience or a strong interest and demonstrated ability to learn Rust quickly.
Experience converting prototypes, research code, simulations, or mathematical algorithms into robust software.
Coursework or experience in algorithms, data structures, operating systems, concurrency, parallel computing, compilers, graph algorithms, or high-performance computing.
Exposure to symbolic AI, neural-symbolic systems, cognitive architectures, causal reasoning, analogical reasoning, reinforcement learning, constraint solving, or simulation systems.
Experience with Python/Rust or Python/C++ interoperability, containers, Kubernetes, Cloud Providers (AWS, GCP, Azure), on-premises systems, CI/CD, databases, graph stores, or messaging systems.
Experience with profiling, benchmarking, deterministic execution, reproducible experiments, or performance-sensitive software.
A collaborative, communicative low-ego working style, intellectual curiosity, testing discipline, and sound judgment when handling confidential or access-controlled intellectual property.

Responsibilities

Translating well-specified Python research modules into readable, tested, maintainable, and performant Rust components.
Building and maintaining unit, integration, regression, simulation, behavioral-equivalence, determinism, and reproducibility tests. QA and Production validation.
Implementing stable interfaces and runtime components within a modular architecture designed to protect proprietary intellectual property.
Profiling CPU usage, memory, latency, and throughput; partnering with senior developers to improve performance and scalability.
Supporting concurrent and parallel execution, Python/Rust interoperability, containerization, CI/CD, observability, and deployment automation.
Helping create components that can support real-time inference, near-real-time reasoning, offline simulations, cloud services, on-premises systems, and embedded or edge environments.
Working closely with research and engineering teammates to clarify requirements, acceptance criteria, and appropriate tradeoffs between algorithm adaptation and reference fidelity.
Documenting designs, interfaces, tests, benchmarks, and operating assumptions so components can be safely understood and maintained.
Learning structured relational, causal, and neural symbolic computation from experienced researchers and applying that knowledge to production software.
Contributing to a collaborative, low-ego team culture centered on curiosity, disciplined engineering, and responsible handling of confidential intellectual property.
Corporate policies, procedures and security standards are complied with while performing assigned duties.
All employees are expected to contribute to a strong Environmental Health and Safety (EHS) culture by following safety policies, identifying hazards, and engaging in continuous improvement.