Interested in this AI/ML Engineer role at TRICO ELECTRIC COOPERATIVE?
Apply Now →Skills & Technologies
About This Role
Join Our Team as a AI Developer at Trico Electric Cooperative!
Posting Period: Tuesday, July 21 \- Until Filled
Annual Salary: $111,500 \- $130,000 DOE
Cooperative Expectations
We are committed to fostering a culture of excellence, where employees are empowered to grow, collaborate, and contribute to meaningful work. Just as we strive to provide 5\-star customer service to our members, we also hold ourselves to the highest standards in how we work and support one another.
What You Will Do:
This role plays a critical part in advancing the organization's data and AI strategy by designing, developing, and maintaining enterprise data warehouses, data lakes, and integration platforms. The position is responsible for creating scalable, secure, and high\-performing data solutions that support business intelligence, advanced analytics, automation, and artificial intelligence initiatives.
The ideal candidate will bring expertise in data architecture, ETL/ELT development, cloud data technologies, and system integrations, ensuring reliable and seamless access to high\-quality data across the organization. By transforming complex data into strategic assets, this role enables data\-driven decision\-making, operational efficiency, and innovation throughout the Cooperative.
Key duties and expectations include, but are not limited to, the following:
- Designs, develops, and implements AI\-powered software that solves real business problems.
- Design, develop, and maintain scalable backend systems to support data warehousing and data lake initiatives.
- Develop and implement integration solutions for seamless data exchange between systems, applications, and platforms.
- Incorporates machine learning (including large language models/LLMs) into scalable applications, owns data/model pipelines end\-to\-end, and partners with product, security, and platform teams to deliver measurable outcomes in production.
- Leads AI development from discovery through deployment, translating business needs into clear technical specifications and milestones.
- Designs, trains, fine\-tunes, and evaluates AI models (e.g. transformers/LLMs, NLP, CV, anomaly detection,
recommendations).
- Builds production\-grade services and APIs that expose AI capabilities, including versioning, contracts, and usage analytics.
- Develops reliable data workflows (ingestion, validation, feature computation, labeling, lineage) and enforces data quality and observability.
- Integrates AI systems with enterprise platforms.
- Documents architectures, datasets, experiments, and models to ensure reproducibility and maintainability.
- Upholds responsible\-AI standards, including privacy, security, explainability, and compliance with applicable frameworks.
- Document technical designs, processes, and standards for the team and stakeholders.
- Perform other related duties as assigned to support departmental and organizational goals.
What You Bring to Trico:
- Bachelor’s degree in Information Technology, Computer Science, Data Science, Engineering, or a related field required.
- 5\+ years of related experience in IT App Support, IT Development, IT Networking, or similar field.
- Certifications in cloud platforms (AWS Certified Data Analytics, Azure Data Engineer, etc.) is preferred.
- Knowledge of data visualization tools (e.g., Tableau, Power BI) for supporting downstream analytics.
- Familiarity with DevOps practices and tools.
- Advanced knowledge of Intelligent Automation concepts including Robotics Process Automation (RPA), automated workflows is preferred.
- Advanced knowledge of Generative AI (e.g., OpenAI, Azure OpenAI, etc.) and Agentic AI concepts and development practices is preferred.
- Knowledge and experience in multiple software development languages (i.e. Java, Javascript, C\#, C\+\+, Python, etc)
- Strong technical aptitude with excellent proficiency in the use of Microsoft Office Solutions (Word, Excel, Outlook).
Why work at Trico
Trico Electric Cooperative is a member\-owned, not\-for\-profit, distribution cooperative headquartered in Marana, Arizona. We service more than 55,000 Members in rural areas surrounding the City of Tucson across three counties in southern Arizona. Trico is dedicated to making a difference in the communities we serve by providing our Members cost\-effective and sustainable energy solutions. In our pursuit of excellence, Trico seeks innovative ways to enhance utility services, ensuring they align with the dynamic needs of our communities. We understand the importance of staying ahead of the curve and are dedicated to exploring cutting\-edge solutions that redefine the provision of critical resources. Our present and future success depends on the creative and dedicated employees of our company who demonstrate Trico’s Core Values of: Service, Dependability, Innovation, and Integrity.
What We Offer
Trico’s success is rooted in our employees’ talent, well\-being, health, and safety. As an electric cooperative and utility, our role in the community is vital, and we recognize the value of a high\-achieving and diverse workforce to serve our Members.
We offer a comprehensive benefits package to meet the needs of our employees and their families and enhance their well\-being. In addition to competitive pay, eligible employees can take advantage of the following benefits:
- Pension Plan (at no cost to the employee)
- 401(k) plan with employer matching
- Medical, vision, dental, and life insurance
- MTO/Catastrophic Leave
- Holiday pay
- Wellness programs (including access to a recreation and fitness facility)
- Tuition assistance for both undergraduate and graduate programs
Equal Opportunity Employer Statement
Trico Electric Cooperative, Inc. is committed to equal employment opportunity regardless of race, color, religion, sex (including pregnancy), gender identity, sexual orientation, national origin, age, disability, genetic information, military status, or any other protected status under applicable federal, state or local law.
Drug/Alcohol Policy Statement
To promote the safety and well\-being of our employees, Members, and the communities we serve, Trico is committed to maintaining a drug/alcohol free work environment. Although marijuana may now be legal in Arizona, except as otherwise specified under Arizona law, Trico considers it to be an illegal drug for the purpose of our drug/alcohol policy because marijuana remains illegal at the federal level. Any candidate found to be impaired during the hiring process or who has the presence of an illegal drug or unauthorized substance in their system during the pre\-employment drug/alcohol test may be disqualified from further consideration in the hiring process.
Work Authorization
All candidates must be legally authorized to work in the United States without sponsorship. Trico does not sponsor employment\-related visas.
Salary Context
This $111K-$130K 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 TRICO ELECTRIC COOPERATIVE, 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 ($120K) sits 45% below the category median. Disclosed range: $111K to $130K.
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.
TRICO ELECTRIC COOPERATIVE AI Hiring
TRICO ELECTRIC COOPERATIVE has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Marana, AZ, US. Compensation range: $130K - $130K.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.