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About This Role
About Us
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:
- Students are our top priority.
- We strive for excellence.
- We thrive on diversity.
- We celebrate collaboration.
- We champion innovation.
- We safeguard freedom of inquiry and expression.
- We nurture the wellbeing of our community.
- We act ethically.
- 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.
Location
Atlanta, Georgia
Department Information
About the School of Office of Information Technology at the Georgia Institute of Technology
Located in the heart of vibrant Atlanta, Georgia, the Partnership for an Advanced Computing Environment (PACE) team defines and manages centralized research computing services at the Georgia Institute of Technology. We facilitate research efforts and foster strategic partnerships to provide Georgia Tech researchers with an unrivaled advantage, empowering them to lead their disciplines for the advancement of science and society across the globe. In addition to high-performance computing, we incorporate emerging cloud, network, data analytics, and storage technologies. Our growing team directly supports faculty, students, and other researchers resulting in a dynamic environment filled with intellectual stimulation and continuous innovation.
Job Summary
The OIT (Office of Information Technology) department at the Georgia Institute of Technology in Atlanta, Georgia, invites applications for the Partnership for Advanced Computing Environment (PACE). Applications will be considered at all ranks. The Partnership for Advanced Computing Environment (PACE) seeks a skilled junior or mid-career Research Scientist to join us. The successful candidate will join the Research Software Engineer (RSE) team in PACE, in collaboration with other teams, and play a key role in building and operating an AI-centric platform, facilitating AI workflow porting on the PACE environment, and developing internal tools to enhance the efficient operation and researchers' scientific/AI workflow. This role will work closely with the Platform and Architecture (Platform) and Cyberinfrastructure (CI) Teams to support GT faculty on research projects and evaluate underlying technologies.
This role requires strong software engineering expertise, system integration experience, excellent communication skills, and the ability to bring innovative solutions to researchers' projects and implement them into deliverables.
Georgia Institute of Technology Research Computing PACE (The Partnership for Advanced Computing Environment) Center is pleased to announce an exciting career opportunity as a Research Software Engineer focused on building and operating AI-centric platforms. This role emphasizes scalable, secure, multi-tenant infrastructure for AI/ML workloads (e.g. JupyterHub, MLflow) supporting everything from interactive development to model training, tracking, and deployment on scalable compute backends (HPC cluster). This position will also serve as a consulting role, collaborating with domain scientists to develop scientific/AI workflows on the PACE system.
This role requires software engineering expertise, system integration experience, excellent communication skills, and the ability to bring innovative solutions to researchers' projects and implement them as deliverables. This role enables reliable, secure, and efficient use of PACE resources for AI/ML workloads by delivering shared platforms, reference workflows, and automation that improve researcher productivity, reproducibility, and operational stability at scale.
Responsibilities
AI-centric Platform Engineering: Build and operate shared AI-centric platforms (e.g., JupyterHub, MLflow) and associated services to enable secure, multi-tenant AI environments for researchers. Integrate identity management, resource quotas, and policy controls; support experiment tracking and reproducibility.
Reliability & Performance: Monitor and improve performance, scalability, and stability of AI services in production. Establish service-level objectives (SLOs) where appropriate; tune systems for GPU utilization, throughput, and latency; and help diagnose workload bottlenecks across compute, storage, and networking.
MLOps & Deployment Enablement: Enable repeatable workflows for training, evaluation, artifact management, and (when applicable) model serving. Define reference patterns for packaging (containers), configuration, and environment management to support reproducible research and reliable rollout of services.
Maintain the user-facing scientific and engineering software stack, including AI, data analytics, and modelling/simulation applications: Develop and optimize the central software stack on the target architecture using containers and/or the automatic software building tool e.g. Spack, EasyBuild.
Documentation & Operational Readiness: Produce clear technical documentation, runbooks, and architecture notes. Communicate progress, risks, and tradeoffs to both technical and non-technical stakeholders; contribute to operational processes.
Stay abreast of Technical Trends: Acquire knowledge through independent study, consultation of textbooks and research papers, and engagement with online training resources relevant to required problem domains.
Work in partnership with other GT Colleges IT groups to support the deployment of scientific/AI applications and workflows for researchers on PACE systems
Closely work with other internal PACE units, including the Platform and Architecture (Platform), Cyberinfrastructure(CI), and Research Computing Facilitation (RCF) Teams, to address researchers needs
Author and publish scientific papers, reports, and presentations to communicate research results and findings to internal and external audiences
Any other task assigned by the supervisor
Required Qualifications
This position vacancy is an open rank announcement. Final job offer will be dependent on candidate qualifications in alignment with Research Faculty ranks as outlined in section 3.2.1 of the Georgia Tech Faculty Handbook (https://www.policylibrary.gatech.edu/faculty-handbook/3.2.1-research-faculty-hiring-and-promotion-guidelines)
Research Scientist I
Bachelors Degree in Computer Science, or related area
Research Scientist II
A Master's degree and three (3) years of relevant full-time experience after completion of that degree, or
A Master's degree and five (5) years of relevant full-time experience after completion of a Bachelor's degree, or
A Doctoral degree in Computer Science, or related area
Preferred Qualifications
The preferred candidate will have:
Master in computational science or related fields.
Excellent written and oral communication skills, with the ability to communicate complex engineering concepts to both technical and non-technical audiences
Proven ability to work independently and as part of a team, with a strong sense of initiative and drive for results
Proficiency in Python and shell scripting (e.g., Bash) for automation and tooling.
Experience with (Nvidia and/or AMD) GPUs and distributed concepts (CUDA stack basics, multi-GPU/multi-node computation) and debugging common performance/failure patterns.
Experience with profiling and troubleshooting tools (e.g., performance analyzers, debuggers) and basic observability concepts (metrics, logs, traces).
Experience with Linux-based compute environments. Familiarity with HPC concepts (schedulers, shared filesystems) and/or distributed AI training is a plus.
Familiarity with complex AI software tool chain building on Linux environment.
Additionally, they will have demonstrated experience in (one or more of the following areas:
Experience with containerization technologies (e.g., Docker, Apptainer, Podman)
Experience with data management, databases (SQL/NoSQL), and distributed systems; comfort designing and operating internal services and APIs.
Experience with AI/ML frameworks such as PyTorch, Ultralytics, and LangChain/LangGraph.
Experience with common AI/ML workflows such as training, fine-tuning, image detection/segmentation, retrieval-augmented generation, and/or agentic workflows.
Experience with inference backend e.g. vLLM, Ollama and Triton
Experience contributing to or supporting open-source software, including PR and code review.
Experience working in developing software for research applications
Experience in software development lifecycle.
Experience in writing and publishing research papers at conferences and journals.
Improving team processes through documentation, automation, and knowledge sharing.
Proposed Salary
Proposed Salary: $53,204 - $110,000. Commensurate with education and experience.
Required Documents to Attach
Applicants should submit the following:
A letter of application
Curriculum vitae
Names and contact information for at least three references.
Application materials should be submitted as PDF.
Contact Information
Requests for information may be directed to Fang (Cherry) Liu at [email protected]
Applications will be considered beginning Oct 15, 2026, but the search will continue until the positions are filled.
USG Core Values
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
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
This is a State Funded Appointment.
Background Check
A successful candidate must be able to pass a background check. Please visit: https://usg.policystat.com/policy/19298143/latest
Salary Context
This $53K-$110K range is in the lower quartile for Research Scientist roles in our dataset (median: $197K across 73 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 8,943 AI roles we're tracking, Research Scientist positions make up 2% of the market. At Georgia Tech, 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 Required
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 708 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($81K) sits 63% below the category median. Disclosed range: $53K to $110K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Georgia Tech AI Hiring
Georgia Tech has 5 open AI roles right now. They're hiring across AI/ML Engineer, Research Scientist, Research Engineer. Positions span Atlanta, GA, US, Smyrna, GA, US. Compensation range: $110K - $170K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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