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About This Role
About Us
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Overview
Georgia Tech prides itself on its technological resources, collaborations, high\-quality student body, and its commitment to building an outstanding and diverse community of learning, discovery, and creation. We strongly encourage applicants whose values align with our institutional values, as outlined in our Strategic Plan. These values include academic excellence, diversity of thought and experience, inquiry and innovation, collaboration and community, and ethical behavior and stewardship. Georgia Tech has policies to promote a healthy work\-life balance and is aware that attracting faculty may require meeting the needs of two careers.
About Georgia Tech
Georgia Tech is a top\-ranked public research university situated in the heart of Atlanta, a diverse and vibrant city with numerous economic and cultural strengths. The Institute serves more than 45,000 students through top\-ranked undergraduate, graduate, and executive programs in engineering, computing, science, business, design, and liberal arts. Georgia Tech's faculty attracted more than $1\.4 billion in research awards this past year in fields ranging from biomedical technology to artificial intelligence, energy, sustainability, semiconductors, neuroscience, and national security. Georgia Tech ranks among the nation's top 20 universities for research and development spending and No. 1 among institutions without a medical school.
Georgia Tech's Mission and Values
Georgia Tech's mission is to develop leaders who advance technology and improve the human condition. The Institute has nine key values that are foundational to everything we do:
1\. Students are our top priority.
2\. We strive for excellence.
3\. We thrive on diversity.
4\. We celebrate collaboration.
5\. We champion innovation.
6\. We safeguard freedom of inquiry and expression.
7\. We nurture the wellbeing of our community.
8\. We act ethically.
9\. We are responsible stewards.
Over the next decade, Georgia Tech will become an example of inclusive innovation, a leading technological research university of unmatched scale, relentlessly committed to serving the public good; breaking new ground in addressing the biggest local, national, and global challenges and opportunities of our time; making technology broadly accessible; and developing exceptional, principled leaders from all backgrounds ready to produce novel ideas and create solutions with real human impact.
The Office of Information Technology (OIT) provides information technology leadership and support to the Georgia Institute of Technology, working in partnership with academic and business units to meet the unique needs of a leading research university. OIT serves as the primary source of enterprise\-wide information technology and telecommunications services in support of students, faculty, staff, and researchers.
Location
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Atlanta, Georgia (In Person in the office)
Job Summary
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Provide enterprise leadership \& vision for IT, data for AI to enable Institute's mission, operations \& strategic objectives. Establish strategic direction for the Institute's digital, data,\& AI capabilities, ensure technology is leveraged as a core enabler of teaching, research, administration, \& student success. Lead \& support campus in understanding and adopting digital \& AI\-enabled ways of working, modernizing systems, processes \& skills to meet evolving institutional needs. Identify \& evaluate emerging technologies, data platforms, AI capabilities, systems software, infrastructure and cybersecurity solutions required for effective digital transformation \& integration across the Institute. Coordinate, facilitate \& consult with academic, research \& admin units to translate business \& mission needs into scalable technology, data \& AI solutions. Responsible for establishing group, departmental or divisional goals; determining resources; assessing performance; \& making pay decisions. Position will interact with executive \& senior leadership, executive\-level internal stakeholders, external service providers, vendors, industry peers \& unit management \& staff. Position will advise \& counsel executive \& Sr leadership, internal stakeholders, unit management \& staff. Position supervises unit management \& staff.
Responsibilities
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Job Duty 1 \-
Lead, develop, and execute an institution\-wide digital, data, and AI strategic plan that advances the Institute's academic, research, and administrative mission. Serve as a strategic business partner to the campus by aligning technology, data, and AI investments with institutional priorities and outcomes. Build and sustain strong relationships with faculty, researchers, staff, students, senior leadership, external service providers, vendors, industry peers, and IT leaders to ensure technology enables innovation, operational excellence, and new ways of teaching, learning, researching, and working. Position information technology, data, and AI as core institutional capabilities that modernize the organization, enhance decision\-making, and drive continuous digital transformation across the Institute.
Job Duty 2 \-
Foster a culture of collaboration, innovation, transparency, and accountability across information technology, data, and AI functions. Lead the development of a service\- and customer\-experience\-focused organization that delivers measurable value to the Institute. Establish modern delivery, product, and portfolio management practices, including effective project and change leadership, to enable rapid, reliable, and scalable outcomes. Define the strategic approach for engaging stakeholders to understand institutional objectives, requirements, and constraints, ensuring technology, data, and AI capabilities are positioned to meet the evolving needs of a global, research\-intensive institution.
Job Duty 3 \-
Serve as the executive portfolio leader for institution\-wide technology, data, and AI initiatives, overseeing the prioritization, adhering to governance, and execution of major programs, projects, and deployments. Review, evaluate, and recommend proposals from academic, research, and administrative units to ensure investments in applications, platforms, infrastructure, data, and AI capabilities align with institutional strategy, architecture, and available resources. Provide oversight for the coordinated management of multiple enterprise information, communications, and digital systems, ensuring delivery of outcomes, effective risk management, and realization of business and mission value.
Job Duty 4 \-
Partner with academic, research, and administrative leaders to modernize business and operational processes across the Institute. Collaboratively identify opportunities to improve efficiency, quality, and scalability through process redesign, data\-driven decision\-making, automation, and AI\-enabled capabilities. Enable and support units in adopting new ways of working by aligning technology, data, change management, and organizational readiness to deliver streamlined, high\-quality, and sustainable outcomes.
Job Duty 5 \-
Serve as a strategic advisor to senior leadership on enterprise technology, data, and AI investment and management. Provide guidance on the evaluation, selection, implementation, and lifecycle management of digital platforms, information systems, data and AI capabilities, and enabling infrastructure. Ensure institutional investments balance innovation, operational excellence, risk, and sustainability, and that strategic and operational systems are aligned with business objectives, mission outcomes, and long\-term value realization.
Job Duty 6 \-
Oversee the performance, quality, and reliability of enterprise technology, data, and AI services to ensure they meet institutional needs and service expectations. Establish strategies, metrics, and governance for monitoring service levels, operational performance, and business value realization. Ensure that organizational processes, systems, and data practices comply with applicable legislation, regulatory requirements, accessibility standards, and institutional policies. Lead the use of performance management, analytics, and continuous improvement practices to evaluate how digital services contribute to institutional effectiveness, risk management, and mission outcomes.
Job Duty 7 \-
Develop, manage, and oversee the university\-wide technology, data, and AI budget, including capital and operating expenditures. Ensure the effective, transparent, and responsible allocation of resources to support institutional priorities, digital transformation, and long\-term sustainability. Provide strategic financial oversight to balance innovation, operational needs, risk management, and return on investment, ensuring technology funding delivers measurable value and advances the Institute's mission.
Job Duty 8 \-
Communicate enterprise technology, data, and AI strategies, policies, standards, and emerging trends across the Institute to executive leadership, management groups, and professional staff. Establish and institutionalize key performance indicators (KPIs), performance metrics, and dashboards to monitor service quality, operational effectiveness, risk, and business value of digital capabilities. Model ethical leadership and responsible stewardship of resources through transparent decision\-making, governance structures, and accountability practices that reinforce trust and institutional integrity.
Job Duty 9 \-
Establish and oversee enterprise data governance and AI governance to ensure trusted, secure, ethical, and compliant use of institutional data and AI\-enabled capabilities. Define and implement policies, standards, and accountability models for data stewardship, privacy, retention, access, and appropriate use, including responsible AI practices. Partner with academic, research, and administrative leaders to promote transparency and confidence in data and AI\-driven decision\-making, while enabling innovation and protecting the Institute's reputation and stakeholders. Provide executive oversight for institutional technology risk management, service resilience, and operational continuity for critical digital capabilities. Ensure appropriate planning, governance, and readiness for disruptions and major incidents, including disaster recovery and business continuity practices. Partner with campus leaders and relevant risk and compliance functions to align security, resilience, and third\-party/vendor risk management with institutional priorities and regulatory obligations, balancing risk reduction with mission enablement.
Job Duty 10 \-
Other duties as assigned.
Required Qualifications
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Educational Requirements
Bachelor's Degree in Information Technology, Computer Science, Information systems or related field, or equivalent combination of education and experience.
Required Experience
Experience including managing a staff of technical professionals; position may require work outside of normal business hours and/or travel Ten years of job related experience.
Preferred Qualifications
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Additional Preferred Qualifications
- Advanced certification in Microsoft Office 365 ecosystem;
- Enterprise Leadership certifications or training, etc.
Preferred Educational Qualifications
Master's Degree in Information Technology, Computer Science, Information Systems or related field.
Preferred Experience
Experience in a research university setting Fifteen years of job related experience; ten years in management role.
Preferred Qualifications
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Experience leading large, enterprise technical teams through the end\-to\-end lifecycle of AI enabled products and services, including design, development, deployment, operations, and ongoing support.
Strong hands\-on understanding of agentic AI development, including agents, workflows, orchestration patterns, and multi model architectures.
Working knowledge of AI platforms and integration layers, such as MCP concepts, AI orchestration layers, AI gateways, and secure enterprise integration patterns.
Practical coding literacy and familiarity with modern AI development tools and environments (e.g., Copilot Studio, Claude Code, and related low code/pro code AI frameworks).
Ability to balance technical depth with executive leadership, effectively partnering across academic, research, administrative, privacy, security, and compliance domains.
Experience operating in higher education, the public sector, or similarly complex and regulated environments is strongly preferred.
Experience in a research University setting 15 years of job\-related experience, 10 years in management role
Advanced certification in Microsoft Office 365 ecosystem
Enterprise Leadership certifications or training.
Proposed Salary
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$100,000 \- $250,000 depending on experience and preferred skills.
Knowledge, Skills, \& Abilities
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ABILITIES
- Proven ability to translate business objectives into information technology initiatives.
- Ability to identify scope and approach to initiatives and formulate short and long term information technology plans and budgets.
KNOWLEDGE
Comprehensive knowledge of business principles and techniques of administration, organization, and management.
SKILLS
- Excellent judgement and decision\-making skills.
- Strong leadership, mentoring, strategic planning, change management, collaboration, and negotiation skills.
- Excellent verbal and written communication skills.
- Strong analytical, critical thinking and problem\-solving skills.
USG Core Values
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The University System of Georgia is comprised of our 25 institutions of higher education and learning as well as the System Office. Our USG Statement of Core Values are Integrity, Excellence, Accountability, and Respect. These values serve as the foundation for all that we do as an organization, and each USG community member is responsible for demonstrating and upholding these standards. More details on the USG Statement of Core Values and Code of Conduct are available in USG Board Policy 8\.2\.18\.1\.2 and can be found on\-line at https://www.usg.edu/policymanual/section8/C224/\#p8\.2\.18\_personnel\_conduct.
Additionally, USG supports Freedom of Expression as stated in Board Policy 6\.5 Freedom of Expression and Academic Freedom found on\-line at https://www.usg.edu/policymanual/section6/C2653\.
Equal Employment Opportunity
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The Georgia Institute of Technology (Georgia Tech) is an Equal Employment Opportunity Employer. The Institute is committed to maintaining a fair and respectful environment for all. To that end, and in accordance with federal and state law, Board of Regents policy, and Institute policy, Georgia Tech provides equal opportunity to all faculty, staff, students, and all other members of the Georgia Tech community, including applicants for admission and/or employment, contractors, volunteers, and participants in institutional programs, activities, or services. Georgia Tech complies with all applicable laws and regulations governing equal opportunity in the workplace and in educational activities.
Equal opportunity and decisions based on merit are fundamental values of the University System of Georgia ("USG") and Georgia Tech. Georgia Tech prohibits discrimination, including discriminatory harassment, on the basis of an individual's race, ethnicity, ancestry, color, religion, sex (including pregnancy), national origin, age, disability, genetics, or veteran status in its programs, activities, employment, and admissions. Further, Georgia Tech prohibits citizenship status, immigration status, and national origin discrimination in hiring, firing, and recruitment, except where such restrictions are required in order to comply with law, regulation, executive order, or Attorney General directive, or where they are required by Federal, State, or local government contract.
Other Information
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This is a supervisory position.
This position does not have any financial responsibilities.
This position will not be required to drive.
This role is considered a position of trust.
This position does not require a purchasing card (P\-Card).
This position will not travel
This position does not require security clearance.
Background Check
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Successful candidate must be able to pass a background check. Please visit http://policylibrary.gatech.edu/employment/pre\-employment\-screening
Salary Context
This $100K-$250K range is above the median 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 Georgia Tech, 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. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($175K) sits 19% below the category median. Disclosed range: $100K to $250K.
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.
Georgia Tech AI Hiring
Georgia Tech has 2 open AI roles right now. They're hiring across AI/ML Engineer, Research Scientist. Based in Atlanta, GA, US. Compensation range: $250K - $250K.
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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