Interested in this AI/ML Engineer role at AAA Mountain West Group?
Apply Now →About This Role
Why Work For Us?
- Great Pay \- opportunity to participate in AAA discretionary annual incentive plan or other incentive plans depending upon position
- 401k Matching – $1 for $1 company match up to 6% of eligible earnings per pay period
- Benefits – Medical, Dental, Vision, wellness program and more!
- Paid Holidays
- Paid Time Off – Team Members accrue paid time off monthly. Depending on position, an additional 24 hours per year are earmarked for volunteer activities.
- Collaborative Environment – AAA will value your contribution to providing exceptional service to our members
- Free AAA Classic Membership
- AAA Product Discounts
- Tuition Reimbursement Program
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At AAA, our Team Members strive to deliver amazing service and help our Members outsmart life’s roadblocks. We believe everything you do outside of work adds to who you are at work.
NOTE: Must Reside in Arizona or Nevada
JOB SUMMARY
The Government Affairs Specialist will be a key player in shaping policy and advocating for the interests of the AAA Mountain West Group (MWG). AAA MWG serves over 6\.7 million Members in Alaska, Arizona, Northern California, Nevada, Montana, Utah and Wyoming. This role will support advancing MWG’s public policy agenda in Arizona and Nevada. As the government affairs contact for this region, you will help develop and implement advocacy strategies, effectively build relationships with government officials, and serve as a safety champion on critical issues such as road safety, emerging vehicle technologies, and smart mobility.
RESPONSIBILITIES / JOB DUTIES
- Advocacy and Lobbying Support:
+ Assist the government affairs team in crafting and executing strategies tailored to state legislatures.
+ Partner with state lobbyists to educate lawmakers and advance MWG’s policy pillars, including road safety, regional transportation improvements, smart mobility and energy, consumer data privacy, and business protection.
+ Draft high\-impact policy materials, fact sheets, position statements for government committees as needed.
- Stakeholder Relations:
+ Build and maintain relationships with an array of stakeholders including government officials, transportation agencies, law enforcement, and community organizations to promote AAA initiatives and partnerships.
+ Collaborate with internal stakeholders, including public affairs staff, subject matter experts, and media relations team to ensure consistent messaging and coordinated advocacy efforts.
+ Represent AAA MWG in various committees, task forces, and public forums, actively participating in key events that strengthen the organization's ability to advocate on behalf of its members.
- Legislative Monitoring \& Reporting:
+ Monitor and analyze proposed legislation, regulatory changes, and emerging issues that could impact AAA members and organizational goals across the assigned states.
+ Synthesize and report timely updates and strategic recommendations to internal teams regarding legislative progress.
+ Identify potential risks and opportunities for engagement across assigned states to inform internal strategy.
KNOWLEDGE / SKILLS / ABILITIES
- Proven experience in monitoring, analyzing, and synthesizing complex legislation and regulatory policies.
- Experience supporting advocacy campaigns and preparing professional lobbying materials (e.g., fact sheets, talking points, position papers).
- Experience building and maintaining professional relationships with diverse stakeholders, including government officials and coalition partners.
EDUCATION, COMPETENCIES, CERTIFICATIONS/LICENSES
- Minimum Qualifications
+ Bachelor's degree in Political Science, Government, Public Administration, Communications, Public Policy, or related field.
+ 5 years of experience in government affairs, lobbying, legislative analysis, public policy, or a relevant role within a state legislature, government agency, or advocacy organization.
- Preferred Qualifications
+ Direct experience working in state legislative or regulatory environments is highly desirable.
+ Experience in policy areas relevant to AAA, such as transportation, mobility, road safety, insurance, or consumer protection.
+ Experience working with contract lobbyists or external consultants.
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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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At AAA Mountain West Group, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
AAA Mountain West Group AI Hiring
AAA Mountain West Group has 3 open AI roles right now. They're hiring across AI/ML Engineer. Positions span North Las Vegas, NV, US, Phoenix, AZ, US, Walnut Creek, CA, US. Compensation range: $238K - $238K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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