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Pay Range: USD $74,550.00 - USD $283,760.00 /Yr. Overview: This position will be located in Huntsville, AL
The Charles D. McCrary Institute for Cyber and Critical Infrastructure Security at Auburn University seeks an experienced Principal Research Scientist/Engineer. This position will provide strategic and technical leadership for the design, development, deployment, and sustainment of advanced artificial intelligence, machine learning, software engineering, and solution architecture capabilities across the organization's research and technology portfolio. This position is responsible for overseeing AI/ML engineering, software delivery, enterprise solution architecture, DevSecOps practices, and secure technology deployment while ensuring scalable, reusable, and mission-focused solutions.
The role leads the development of innovative AI-enabled capabilities supporting government, defense, and applied research initiatives, including AI-powered malware analysis, open-source intelligence (OSINT) platforms, maritime and rural health technology solutions, and other emerging technology applications. The position serves as a key technical leader in building internal engineering capacity, advancing software and AI modernization efforts, and transitioning critical architecture and development knowledge from external professional service providers to sustainable employee-owned capabilities. Through strategic planning, technical oversight, and team development, this role ensures the delivery of secure, high-quality solutions that support current and future mission requirements while strengthening the organization's long-term technical maturity and operational effectiveness. Responsibilities:
- Set and maintain the technical roadmap for AI, data, and software capabilities across Edge Lab programs.
- Lead multidisciplinary research and development projects from problem framing and experimental design through prototype, validation, deployment, and transition.
- Design and review software architectures, APIs, data pipelines, model-serving patterns, user-facing applications, and integration approaches.
- Establish engineering practices for source control, automated testing, CI/CD, secure software development, documentation, code review, and release management.
- Develop responsible AI and MLOps practices covering data governance, evaluation, model risk, monitoring, reproducibility, privacy, and lifecycle management.
- Provide hands-on technical contributions in appropriate programming languages, cloud/on-premises platforms, AI frameworks, and data technologies.
- Guide selection and integration of foundation models, machine-learning methods, retrieval systems, agents, and other AI techniques based on mission need and evidence.
- Partner with the Technology Architect’s and Senior Cybersecurity Analyst's to ensure solutions are resilient, secure, observable, and deployable in customer environments.
- Mentor engineers, researchers, students, and technical staff; assign work, review technical quality, and expand bench strength.
- Develop technical concepts, proposals, budgets, schedules, demonstrations, reports, publications, and executive/customer briefings.
- Lead knowledge transfer from software and AI consultants and assume ownership of reusable code, platforms, and technical decisions.
Qualifications: Must be a U.S. Citizen
Focus of Education: PhD from an accredited institution Engineering, Science, Management Information Science (MIS), or related technical field. Scope of Expereince: Experience for Levels II-VII should be in engineering and research practices and principles or science-based programs.* Level I: No experience required
- Level II: 2 years of professional experience
- Level III: 4 years of professional experience
- Level IV: 6 years of professional experience
- Level V: 8 years of professional experience
- Level VI: 10 years of professional experience
- Level VII:12 years of professional experience
Substitutions for Experience:
Candidates with a Bachelor’s or Master’s degree may substitute relevant experience toward the PhD requirement at the rate of two (2) years relevant experience per year of required education. Minimum Knowledge, Skills, and Abilities:
- Knowledge of research principles, laboratory techniques, and safety procedures.
- Fully competent in all conventional aspects of subject matter or functional areas of assignments.
Why Work at Auburn:
- Life-Changing Impact: Our work changes lives through research, instruction, and outreach, making a lasting impact on our students, our communities, and the world.
- Culture of Excellence: We are committed to leveraging our strengths, resources, collaboration, and innovation as a top employer in higher education.
- We’re Here for You: Auburn offers generous benefits, educational opportunities, and a culture of support and work/life balance.
- Sweet Home Alabama: The Auburn/Opelika area offers southern charm, vibrant downtown scenes, top-ranked schools, and easy access to Atlanta, Birmingham, and the Gulf of Mexico beaches.
- A Place for Everyone: Auburn is committed to fostering an environment where all faculty, staff, and students are welcomed, valued, respected, and engaged.
- Ready to lead and shape the future of higher education? Apply today! War Eagle!
Equal Opportunity Compliance Statement: It is our policy to provide equal employment and education opportunities for all individuals without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, gender expression, pregnancy, age, disability, protected veteran status, genetic information, or any other classification protected by applicable law. Please visit the Office of Equal Opportunity Compliance's website to learn more.
Salary Context
This $74K-$283K range is below the median for Research Scientist roles in our dataset (median: $199K across 63 roles with salary data).
Role Details
About This Role
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.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 9,079 AI roles we're tracking, Research Scientist positions make up 2% of the market. At Auburn University, this role fits into their broader AI and engineering organization.
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 the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering 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.
Skills in Demand for This Role
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.
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.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 749 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($179K) sits 19% below the category median. Disclosed range: $74K to $283K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Auburn University AI Hiring
Auburn University has 2 open AI roles right now. They're hiring across Research Scientist, Research Engineer. Based in Auburn University, AL, US. Compensation range: $189K - $283K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
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.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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