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About This Role
- Alabama, United States
- Libraries
- Tenure/Tenure\-Track Faculty
- Closing at: Sep 11 2026 \- 22:55 CDT
Department/Organization
219101 \- University Libraries
Rank
Assistant/Associate Professor
Position Summary
The University of Alabama Libraries seeks a creative and motivated individual to join the Research Computing Services team as the Artificial Intelligence (AI) Librarian. Reporting to the Director of Research Computing Services, this position serves a dual role, supporting AI\-assisted workflows and services within University Libraries and participating in multimodal library and information literacy instruction.
Detailed Position Information
The AI Librarian will collaborate with University Libraries colleagues and campus partners to identify, develop, and implement AI\-driven solutions that enhance library workflows and services. Areas of focus may include AI\-assisted applications for internal library operations, such as collection management, interlibrary loan, cataloging, metadata generation, transcription, indexing, and workflow automation, as well as end\-user services, such as custom library chatbots, and recommendation and discovery systems.
Responsibilities also include providing consultations, instruction, training, outreach, and support for initiatives related to AI and related technologies within various phases of research and learning across campus. This position will develop and maintain AI and research computing related educational tutorials and documentation.
The AI Librarian will assist in the oversight of University Libraries student developers who provide research computing services such as workshops, walk\-in coding support, and developing custom scripting for computational teaching and research projects. The AI Librarian will develop AI and related use\-cases for student developer projects that support AI and computational research methods internally within University Libraries and across the disciplines supporting faculty, staff, and students.
The AI Librarian will serve as a subject area liaison based on the evolving needs for research and instructional support. This position will be responsible for developing a robust instruction and outreach program, both in\-person and online, while also offering AI related software application training and support services based on the assigned disciplines. This position will work collaboratively within University Libraries to promote and integrate research computing and data services into library instruction and workshops across the disciplines. Liaisons support both in\-person and virtual instruction, reference, and outreach in assigned areas and will be expected to collaborate with teaching faculty on library assignments and actively create digital learning objects in support of teaching and research.
The AI Librarian will be expected to develop a robust suite of structured information instruction and reference services. All liaisons participate in UA’s First Year Experience library instruction and weekly chat service. Moreover, all liaisons within University Libraries are actively incorporating AI as appropriate into their instruction, for example teaching emerging AI tools within library databases. The AI Librarian will coordinate AI activities among liaisons and across University Libraries, assist with developing AI literacies, as well as provide advanced AI support, for example assistance with locally run generative AI models for students and faculty or use of custom AI agents within instruction.
This position works with a wide range of internal and external stakeholders and is expected to build and sustain relationships within University Libraries, with campus partners such as the High\-Performance Computing and Data Center and the Alabama Center for the Advancement of Artificial Intelligence, and with colleges and universities across the state, region, and nation.
The person in this position will be encouraged to pursue grant writing opportunities and submission of grants relevant to the mission of University Libraries and The University of Alabama. The successful candidate must possess the ability to approach change, ambiguity, and complex problems that are typical of a research university setting.
Responsibilities of the position may change as University Libraries continues to evolve.
SALARY/BENEFITS: 12\-month tenure track faculty appointment at the Assistant or Associate Professor rank. Salary is $100,000\.00 \- $120,000\.00, commensurate with qualifications, experience, and advanced degrees. Strong benefits, including professional development support, tuition fee waiver, and matching retirement contributions.
Minimum Qualifications
- Master's in Library \& Information Sciences from an ALA\-accredited institution or a doctoral degree in a relevant field.
- Experience with Python and scientific computing libraries including NumPy, Pandas, and scikit\-learn.
- Familiarity with additional scientific computing or data science languages such as R, Julia, C\+\+, Wolfram, or MATLAB.
- Experience managing development environments, including tools such as conda, containers, and version control systems.
- Experience developing or customizing AI tools such as creating custom agent instructions, configuring AI assistants, or using AI development APIs.
- Knowledge of the AI/ML model landscape, including generative AI, computer vision, multimodal models, natural language processing, and other domain\-specific models.
- Familiarity with Linux based research computing environments including command line tools and connecting to remote servers.
- Ability and interest to serve as a subject area expert in STEM liaison areas.
- Ability to learn and apply new technical skills and tools through self\-directed learning.
- Ability to conceptualize, articulate, and implement short and long\-range goals.
- Ability to work independently and as a team member to solve problems, using sound judgment in decision\-making according to an established timeframe.
- Commitment to conduct research and scholarship consistent with the requirements of a tenure track appointment; commitment to engage in continuing profession development and service.
- Excellent verbal and written communication, including associated skills such as listening, negotiating, and adapting.
- Demonstrated ability to work effectively in a complex and changing environment
- Proven ability to work both independently and collaboratively and complete tasks according to an established timeframe while managing multiple priorities and consistently meeting deadlines.
- Adaptability, flexibility, and willingness to engage in continuous learning to meet the changing needs of library users.
- Ability to support and enhance a robust learning and working environment.
- Responsibilities change as the University Libraries continue to evolve.
- Ability to meet the requirements for tenure and promotion.
- Evidence of ability to engage in research, librarianship, and service consistent with the University’s and Libraries’ guidelines for faculty promotion and tenure.
Preferred Qualifications
- Doctoral degree in a STEM or related quantitative social sciences field. • Experience with teaching or creating computing related tutorials. • Experience running local language models using open\-source tools such as llama\-cpp or Ollama. • Experience with LLM\-based retrieval\-augmented generation (RAG) workflows. • Experience with model libraries and frameworks such as PyTorch and Transformers for developing or running AI/ML models. • Experience with natural language processing. • Experience working with high\-performance computing (HPC). • Experience submitting grant proposals. • Evidence of an active published research portfolio. • Knowledge of reference/instructional services in an academic library setting. • Knowledge of trends and services in academic libraries to support undergraduate, graduate, and online education • Knowledge of current and emerging trends in information literacy instruction and information technologies. • Awareness of new and emerging technologies and how they can be utilized in an academic library. • Ability to successfully initiate, track, and manage projects. • Understanding of ways to market and promote instruction, collections, and services to assigned liaison areas and various programs.
Instructions and Required Materials for Application
Applications are accepted online only at https://careers.ua.edu. Click Faculty Jobs, then University Libraries. Please include your application, Curriculum Vitae, cover letter, and names, addresses, phone numbers, and e\- mail addresses of three references, including one current supervisor. Consideration of applications will begin immediately and will continue until position is filled. Applications received by September 11, 2026, are assured of receiving full consideration. For questions regarding the search, contact Michael Arthur, Senior Associate Dean, at [email protected].
About the Division/College/School
The University of Alabama Libraries, a system of seven separate discipline\-related libraries, is proud to support the research enterprise at the University of Alabama via a comprehensive and integrated network of resources, services, and technologies designed to meet the academic and research needs of students, faculty, and staff. We take pride in serving as a hub for innovation, knowledge creation and dissemination, research assistance, and collaborative learning. As a U.S. Government Documents Regional Depository since 1860, University Libraries also serves the public and our local community.
The University of Alabama Libraries maintains memberships in the Association of Research Libraries, the Center for Research Libraries, the Greater Western Library Alliance (GWLA), the Coalition of Networked Information, centerNET, LYRASIS, HathiTrust, the Association of Southeastern Research Libraries, LOCKSS, the Network of Alabama Academic Libraries, and the Alabama Digital Preservation Network.
University Libraries provides strong mentorship for faculty and staff, with ongoing collaborative opportunities, and administrative support for innovative services and ideas. We promote and administer a robust professional development environment that supports faculty research and conference travel, and we are invested in academic freedom with teaching and research. We are heavily invested in performing the same high value research that our stakeholders produce, and that assists in our data\-driven strategic planning for the future. Our staff routinely update and maintain cutting edge programs of service in support of our stakeholders. Our faculty librarians have developed a record\-breaking instruction program, including a series of research data services and workshops, that consistently perform at the top of the SEC.
UA is located in Tuscaloosa, a metropolitan area of over 250,000, with a vibrant economy, a moderate climate, and reputation across the South as an innovative, progressive community with an excellent quality of life. If working with a talented group of professionals who value service, innovation, and high achievement, earning a nationally competitive starting salary, in a thriving college town, with a low cost of living, close to Birmingham, Atlanta, Nashville, New Orleans, and the Gulf Coast sounds interesting to you, start your application process with us to learn more!
Prior to employment the successful candidate must pass a pre\-employment background investigation.
About the University
The University of Alabama is located in Tuscaloosa, Alabama, named one of Travel \+ Leisure’s 25 Best College Towns and Cities in the U.S. As one of the nation’s premier universities, UA offers bachelor’s, master's and doctoral degrees in nearly 200 fields of study. With more than 1,400 acres of tree\-lined academic core campus and over 300 state\-of\-the art facilities, UA has been ranked among the most beautiful and most impressive college campuses in the South, in the state of Alabama and in the nation.
In Fall 2023, the Capstone set a new enrollment record with more than 39,000 students, including more than 8,200 in the freshman class. The current enrollment includes students from every county in Alabama, every state in the nation and 92 countries around the world. More than 1,100 National Merit Scholars are currently enrolled, making UA one of the largest enrolling institutions of the scholars in the country.
UA was recently recognized as a Top Producing Institution of Fulbright U.S. students for the seventh time in nine years, as well as a Top Producing Institution of Fulbright U.S. Scholars for the first time. UA is one of only 12 universities in the nation to receive both honors.
For reasons like this, the University made Forbes list of America’s Top Colleges for 2023 and Time magazine’s list of Top 50 Best Colleges for Future Leaders. It also made Princeton Review’s list of Top Value Colleges.
UA is also designated among the top doctoral research universities in the United States in the Carnegie Classification of Institutions of Higher Education. One of the fastest growing major research institutions in the nation, UA saw a 21% increase in sponsored awards in the 2023 fiscal year.
Since 2015, UA has invested over $1\.1 billion in the physical campus, adding more than 2\.55 million gross square feet of space, over 150 new research\-intensive faculty, signature research areas (e.g., “The Alabama Research Institutes”), and a growing number of partnerships with industry and with state and federal agencies.
The University employs nearly 2,100 faculty and over 4,500 staff, with 52 UA researchers included in the National Academy of Inventors. An additional 40 current faculty have received the NSF CAREER Award, the nation’s most prestigious recognition of top performing young scientists in disciplines ranging from nanoscience and engineering to biological sciences.
Background Investigation and EEO Statement
Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre\-employment background investigation and information obtained from social media and other internet sources. A prior conviction reported as a result of the background investigation DOES NOT automatically disqualify a candidate from consideration for this position. A candidate with a prior conviction or negative behavioral red flags will receive an individualized review of the prior conviction or negative behavioral red flags before a hiring decision is made.
Equal Employment Opportunity: The University of Alabama is an Equal Employment/Equal Educational Opportunity Institution. All qualified applicants will receive consideration for employment or volunteer status without regard to any legally protected basis and will not be discriminated against because of their protected status. Applicants and employees of this institution are protected under Federal law from discrimination on several bases. More information is available in the EEOC’s Know Your Rights: Workplace (https://www.eeoc.gov/sites/default/files/2023\-06/22\-088\_EEOC\_KnowYourRights6\.12ScreenRdr.pdf) discrimination is illegal poster.
The University of Alabama affirms its longstanding commitment to institutional neutrality, free speech, and academic freedom.
Salary Context
This $100K-$120K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At University of Alabama, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($110K) sits 49% below the category median. Disclosed range: $100K to $120K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
University of Alabama AI Hiring
University of Alabama has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in AL, US. Compensation range: $120K - $120K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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