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About This Role
Employment Type:
ALLETE \- Non\-Union
FLSA Status:
Exempt
AI Engineer II
$82,000 \- $102,000 \| Hybrid with in\-person reporting to Duluth, MN
Shape the future of AI at ALLETE. Build and deliver practical AI solutions that create real business value.
We're looking for a skilled professional to accelerate the delivery of AI solutions aligned with our enterprise strategy and business objectives. In this role, you’ll work hands\-on with modern AI technologies to build applications, agents, and automations from concept through production. Partnering with teams across the enterprise, you’ll solve business challenges and deliver secure, accessible, and scalable solutions that create meaningful impact.
What You’ll Do
- Design, build, and deploy AI\-enabled applications, agents, automations, and integrations that address business needs.
- Translate business requirements into secure, scalable, and supportable AI solutions, leveraging enterprise systems, APIs, databases, Microsoft 365, Azure, and Power Platform technologies.
- Partner with AI Data Engineers and cross\-functional teams to ensure data readiness, quality, and seamless integration across solutions.
- Support the full AI solution lifecycle, including discovery, design, development, deployment, ongoing support, and continuous improvement.
- Develop and maintain scalable AI solutions using reusable patterns, prompt engineering, RAG, embeddings, and workflow automation while applying responsible AI, security, and privacy best practices.
Required Education and Experience
- Bachelor’s degree in computer science, information technology, data science, software engineering, computer engineering, or information systems required.
- Four or more years of experience in software development, application development, systems integration, automation, cloud technology, or related IT delivery required.
- This position may be subject to assessment of skills, job match and/or aptitude.
Preferred Experience
- Experience working with SQL and one or more programming or scripting languages such as Python, PySpark, JavaScript/TypeScript, C\#, .NET, or similar.
- Experience working with databases, APIs, cloud services, and enterprise integrations.
- Familiarity with AI technologies such as generative AI, prompt design, retrieval augmented generation (RAG), agents, or workflow automations.
- Strong analytical, troubleshooting, communication, testing, documentation, and operational support practices.
Ready to help shape the future of AI at ALLETE? Apply today—we’re hiring now to support immediate AI solution delivery across the business.
ALLETE is a values‑driven energy company advancing a sustainable future through its nationwide family of clean‑energy businesses and regulated utilities, all grounded in a culture of integrity, safety, people, and the planet. Across the organization, teams contribute to meaningful work that supports reliable energy, innovative infrastructure, and a long‑term commitment to sustainability.
We’re headquartered in Duluth, Minnesota, which is located on the scenic shores of Lake Superior. Duluth offers a unique combination of professional opportunity and outdoor adventure and is a welcoming place to live and build your career.
The expected annual compensation range for this position is $82,000 \- $102,000\. Compensation offered will vary based on knowledge, skills, experience, and market conditions.
This position qualifies for a comprehensive benefits package including:
- Incentive Programs
- Retirement Benefits
- Medical, Dental \& Vision Plans
- Health Savings Account
- Flexible Spending Accounts
- Life Insurance
- Disability
- Tuition Reimbursement
- Voluntary Benefits
- Paid Absences, and more.
This position is posted externally as an AI Engineer II and is internally classified as a Programmer Analyst II.
Employer will not sponsor Visas for position.
*External applicants must apply online via www.allete.com/careers.*
*This job posting will be available for application until the position has been filled OR the posting close date noted herein, whichever date is earlier.*
*ALLETE is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.*
*If you are an individual with disabilities who needs accommodation or you are having difficulty using our website to apply for employment, please contact our Human Resources department at 218\-723\-3921\.*
*EEO/AA/F/M/Vet/Disabled*
Salary Context
This $82K-$102K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At ALLETE, 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 Required
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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($92K) sits 58% below the category median. Disclosed range: $82K to $102K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
ALLETE AI Hiring
ALLETE has 2 open AI roles right now. They're hiring across AI/ML Engineer, Data Engineer. Based in Duluth, MN, US. Compensation range: $102K - $102K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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