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Job Description:
AI Guardrails & Profile Engineer
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 an AI Guardrails & Profile Engineer, you will shape how 3M's conversational AI answers customer and employee questions safely and accurately. You will author and maintain the guardrail policies and subject matter expert (SME) profiles that govern what the AI can and cannot say, test those changes rigorously before each release, and partner with legal, product safety, and division experts to keep answers trustworthy. Your work directly protects customers and 3M while expanding the range of questions the AI can usefully answer.
Key Responsibilities
- Author and maintain conversational AI guardrail policies and subject matter expert (SME) profiles, translating business, legal, and safety requirements into structured, testable instructions
- Design and run quality assurance (QA) and regression testing for AI profiles and guardrails, documenting defects and verifying fixes before each release
- Manage change control across QA and development environments using Jira and Git, including tickets, pull requests, and version tracking
- Partner with subject matter experts, legal, and product safety reviewers to validate and approve AI response behavior
- Analyze conversation history and user feedback to identify coverage gaps and continuously improve answer accuracy and completeness
- Maintain versioned policy catalogs and support release, rollback, and incident handling for guardrail changes
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 (completed and verified prior to start)
- Five (5) years of combined experience in digital product, content governance, quality assurance testing, prompt or conversational AI design, or technical writing in a private, public, government or military environment
Additional qualifications that could help you succeed even further in this role include:
- Experience authoring or testing conversational AI, prompts, or structured content policies
- Hands-on familiarity with Jira and Git (tickets, pull requests, version control)
- Strong analytical, quality assurance, and defect-tracking skills with high attention to detail
- Proven cross-functional collaboration and stakeholder management
- Ability to translate legal, safety, and business requirements into clear, testable rules
- Working knowledge of, or the ability to quickly learn, 3M product and industrial/safety domains
Work location: This role has on-site working model, with the employee working at least four days a week in the office at 3M Center, located in Maplewood, MN.
Travel: No
Relocation: No
Must be legally authorized to work in country of employment without sponsorship for employment visa status (e.g., H1B status).
Supporting Your Well-being
3M offers many programs to help you live your best life – both physically and financially. To ensure competitive pay and benefits, 3M regularly benchmarks with other companies that are comparable in size and scope.
Chat with Max
For assistance with searching through our current job openings or for more information about all things 3M, visit Max, our virtual recruiting assistant on 3M.com/careers.
Applicable to US Applicants Only:The expected compensation range for this position is $164,612 - $201,193, which includes base pay plus variable incentive pay, if eligible. This range represents a good faith estimate for this position. The specific compensation offered to a candidate may vary based on factors including, but not limited to, the candidate’s relevant knowledge, training, skills, work location, and/or experience. In addition, this position may be eligible for a range of benefits (e.g., Medical, Dental & Vision, Health Savings Accounts, Health Care & Dependent Care Flexible Spending Accounts, Disability Benefits, Life Insurance, Voluntary Benefits, Paid Absences and Retirement Benefits, etc.). Additional information is available at: https://www.3m.com/3M/en_US/careers-us/working-at-3m/benefits/. Good Faith Posting Date Range 10/16/2026 To 11/15/2026 Or until filled All US-based 3M full time employees will need to sign an employee agreement as a condition of employment with 3M. This agreement lays out key terms on using 3M Confidential Information and Trade Secrets. It also has provisions discussing conflicts of interest and how inventions are assigned. Employees that are Job Grade 7 or equivalent and above may also have obligations to not compete against 3M or solicit its employees or customers, both during their employment, and for a period after they leave 3M. Learn more about 3M’s creative solutions to the world’s problems at www.3M.com or on Instagram, Facebook, and LinkedIn @3M. Responsibilities of this position include that corporate policies, procedures and security standards are complied with while performing assigned duties. Safety is a core value at 3M. 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. Pay & Benefits Overview: https://www.3m.com/3M/en_US/careers-us/working-at-3m/benefits/ 3M does not discriminate in hiring or employment on the basis of race, color, sex, national origin, religion, age, disability, veteran status, or any other characteristic protected by applicable law.Please note: your application may not be considered if you do not provide your education and work history, either by: 1) uploading a resume, or 2) entering the information into the application fields directly.
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Salary Context
This $164K-$201K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 2094 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 10,827 AI roles we're tracking, AI/ML Engineer positions make up 77% of the market. At 3M, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,160 based on 13,809 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($182K) sits 14% below the category median. Disclosed range: $164K to $201K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,300; VP: $236,450.
3M AI Hiring
3M has 6 open AI roles right now. They're hiring across AI/ML Engineer, Research Engineer. Positions span Maplewood, MN, US, Austin, TX, Austin, TX, US. Compensation range: $100K - $351K.
Location Context
Across all AI roles, 6% (665 positions) offer remote work, while 10,097 require on-site attendance. Top AI hiring metros: New York (3,262 roles, $221,000 median); San Francisco (2,767 roles, $260,600 median); Los Angeles (1,585 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 10,827 open positions tracked in our dataset. By seniority: 122 entry-level, 5,256 mid-level, 3,922 senior, and 1,527 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (665 positions). The remaining 10,097 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 10,827 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,288), AI Software Engineer (548), AI Product Manager (471). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (122) are outnumbered by mid-level (5,256) and senior (3,922) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,527 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (665 positions), with 10,097 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,111, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,093 postings), Aws (1,100 postings), Azure (910 postings), Rag (863 postings), Gcp (680 postings), Pytorch (549 postings), Claude (532 postings), Kubernetes (511 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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