University of Utah is actively hiring for 7 AI and machine learning positions across AI/ML Engineer (4), Research Scientist (2), and Data Scientist (1) roles. Posted salary ranges span $105K - $135K, with 71% of listings disclosing compensation. The median posted ceiling sits at $125K. Positions are based in Salt Lake City, UT, US. The most frequently requested skills across these postings are Python, Aws, Azure, Claude, Gemini. Mid-level roles account for 85% of openings.
Skills & Technologies
Locations
Salt Lake City, UT, US
Hiring by Role Category
Open Positions (7)
Research Scientists (non-PhD)
AI Engineer III
Research Scientists (PhD)
AI Engineer
AI Platform Engineer III
Senior Machine Learning Engineer
Data Scientists
What University of Utah's hiring tells you
7 open AI roles across 3 role types puts this company in the scaling phase: past the initial proof of concept, building out a real team. Expect more structure than a startup but less bureaucracy than a major. Good fit for engineers who want ownership without building from zero. Posted compensation range ($105K - $135K) suggests transparent and competitive pay practices.
The skill mix here leans toward Python in Research Scientist roles. That is a clue about what University of Utah is building: teams hire for the work in front of them, not the work they wish they were doing.
Questions worth asking in the University of Utah interview loop
The signals above come from public job postings. The signals you actually need come from the conversation. A few questions calibrated to this company's tier:
- What problem did the first AI hire solve, and how has scope grown since?
- Where does AI sit in the engineering org, and who owns the budget?
- What is the on-call expectation for AI systems? (If unclear, that means it has not happened yet.)
University of Utah AI and ML Hiring
University of Utah has 7 active AI and ML roles in our dataset. Open positions span Research Scientist, AI/ML Engineer, Data Scientist. Compensation ranges from $105K - $135K across disclosed roles. Roles are based in Salt Lake City, UT, US.
Salary Benchmarks
The market median for AI roles is $215,000. Research Scientist roles pay a median of $222,200 across the market. AI/ML Engineer roles pay a median of $215,000 across the market. Data Scientist roles pay a median of $192,450 across the market. Top-quartile AI compensation starts at $267,900.
Skills University of Utah Looks For
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
AI Role Categories
Research Scientist
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Market compensation for Research Scientist roles: $222,200 median across 310 positions with disclosed pay.
AI/ML Engineer
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.
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.
Market compensation for AI/ML Engineer roles: $215,000 median across 5,661 positions with disclosed pay.
Data Scientist
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Market compensation for Data Scientist roles: $192,450 median across 678 positions with disclosed pay.
The AI Job Market Today
The AI job market spans 4,109 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,893), Data Scientist (308), AI Software Engineer (293). 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 (120) are outnumbered by mid-level (1,975) and senior (1,609) 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 405 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (642 positions), with 3,444 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 $215,000. Top-quartile roles start at $267,900, and the 90th percentile reaches $322,980. 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 $275,000 median, while AI Consultant roles sit at $148,848. 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 (2,102 postings), Aws (1,190 postings), Azure (917 postings), Rag (897 postings), Gcp (673 postings), Prompt Engineering (582 postings), Pytorch (581 postings), Kubernetes (538 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.
AI Hiring Overview
The AI job market has 4,109 open positions tracked in our dataset. By seniority: 120 entry-level, 1,975 mid-level, 1,609 senior, and 405 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (642 positions). The remaining 3,444 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $267,900. The 90th percentile reaches $322,980. Highest-paying categories: AI Safety ($275,000 median, 33 roles); Research Engineer ($272,100 median, 204 roles); AI Engineering Manager ($250,000 median, 19 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Frequently Asked Questions
Frequently Asked Questions
Related Resources
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.