Inside Higher Ed ยท 5 hours ago
Research Scientist- Open Rank (Working Title: Research Assistant Professor in Artificial Intell...
Atlanta, GA
Full-time
Onsite
Mid, Senior Level
3+ years expGeorgia Tech is a top-ranked public research university located in Atlanta, Georgia. The Research Scientist role focuses on leading advanced research in Artificial Intelligence, including laboratory management and project oversight.
Digital MediaEducationHigher EducationJournalismRecruiting
Responsibilities
Research Leadership in Foundation Models, World Models, and Frontier AI
Lead and execute advanced research programs in large-scale AI, including foundation model architectures, multimodal representation learning, world models, agentic systems, and self-supervised learning at scale
Design and evaluate new training algorithms, model architectures, and scalable pipelines for language, vision, audio, robotics, simulation, and multi-agent environments
Develop GPU-, TPU-, and cluster-optimized training frameworks, distributed training systems, and inference-time optimization pipelines for next-generation AI models
Publish high-impact papers in top AI/ML venues, release open-source tools, and contribute to Georgia Tech's AI research leadership and national strategic priorities
Lab Management and AI Compute Infrastructure Operations
Oversee daily operations of the AI research lab, including GPU clusters, high-performance storage, distributed training stacks, and data governance frameworks
Manage, maintain, and expand high-performance compute infrastructure: multi-node GPU clusters, distributed data loaders, RL/simulation environments, and model evaluation frameworks
Ensure safety, compliance, documentation, model governance, data integrity, and continuous uptime of compute and AI assets
Build automated pipelines for model training, experiment reproducibility, dataset generation, benchmarking, and large-scale evaluation
Affiliate Engagement, Business Development, and Partnerships
Engage, onboard, and support affiliate companies participating in the AI and foundation model research program
Serve as a technical liaison for affiliates across AI labs, cloud providers, robotics companies, semiconductor partners, government agencies, and enterprise AI users
Define joint research thrusts, scoping documents, datasets, deliverables, evaluation protocols, and IP structures for partner organizations
Coordinate demos, campus visits, model showcases, and affiliate meetings to support collaboration and knowledge transfer
Project Management and PhD Mentorship
Mentor PhD students, postdocs, and research engineers working on foundation models, world models, agentic systems, and large-scale representation learning
Manage multi-PI, multi-institution, and affiliate-funded AI research efforts, ensuring timely execution, publications, deliverables, reporting, and stakeholder satisfaction
Provide technical direction on model design, dataset creation, training strategies, evaluation, experiment planning, scheduling, milestones, and results dissemination
Qualification
Required
Research Leadership in Foundation Models, World Models, and Frontier AI
Lead and execute advanced research programs in large-scale AI, including foundation model architectures, multimodal representation learning, world models, agentic systems, and self-supervised learning at scale
Design and evaluate new training algorithms, model architectures, and scalable pipelines for language, vision, audio, robotics, simulation, and multi-agent environments
Develop GPU-, TPU-, and cluster-optimized training frameworks, distributed training systems, and inference-time optimization pipelines for next-generation AI models
Publish high-impact papers in top AI/ML venues, release open-source tools, and contribute to Georgia Tech's AI research leadership and national strategic priorities
Oversee daily operations of the AI research lab, including GPU clusters, high-performance storage, distributed training stacks, and data governance frameworks
Manage, maintain, and expand high-performance compute infrastructure: multi-node GPU clusters, distributed data loaders, RL/simulation environments, and model evaluation frameworks
Ensure safety, compliance, documentation, model governance, data integrity, and continuous uptime of compute and AI assets
Build automated pipelines for model training, experiment reproducibility, dataset generation, benchmarking, and large-scale evaluation
Engage, onboard, and support affiliate companies participating in the AI and foundation model research program
Serve as a technical liaison for affiliates across AI labs, cloud providers, robotics companies, semiconductor partners, government agencies, and enterprise AI users
Define joint research thrusts, scoping documents, datasets, deliverables, evaluation protocols, and IP structures for partner organizations
Coordinate demos, campus visits, model showcases, and affiliate meetings to support collaboration and knowledge transfer
Mentor PhD students, postdocs, and research engineers working on foundation models, world models, agentic systems, and large-scale representation learning
Manage multi-PI, multi-institution, and affiliate-funded AI research efforts, ensuring timely execution, publications, deliverables, reporting, and stakeholder satisfaction
Provide technical direction on model design, dataset creation, training strategies, evaluation, experiment planning, scheduling, milestones, and results dissemination
Bachelor's Degree in Electrical Engineering, Physics, or related area
A Master's degree and three (3) years of relevant full-time experience after completion of that degree
A Master's degree and five (5) years of relevant full-time experience after completion of a Bachelor's degree
A Doctoral degree
A Master's degree and seven (7) years of relevant full-time experience after completion of that degree
A Master's degree and nine (9) years of relevant full-time experience after completion of a Bachelor's degree
A Doctoral degree and four (4) years of relevant full-time experience after completion of a Bachelor's degree
Preferred
PhD in Computer Science, Electrical and Computer Engineering, Machine Learning, or a closely related field with emphasis on AI or large-scale model development
Strong research record in foundation models, world models, representation learning, multimodal AI, distributed training, or agentic systems
Hands-on experience with large-scale model training using GPUs/TPUs, distributed systems, deep learning frameworks (PyTorch, JAX, TensorFlow), and data pipelines
Demonstrated experience mentoring students or leading technical AI teams
Strong communication and presentation skills for both technical and non-technical audiences
Company
Inside Higher Ed
Inside Higher Ed is the online source for news, opinion, and jobs related to higher education.
51-200 employees
Funding
Current Stage
Growth StageTotal Funding
unknown2022-01-10Acquired
2006-08-31Series Unknown
Leadership Team
Stephanie Shweiki
Director, Foundation Partnerships
Recent News
Research & Development World
2025-05-03
Business Standard India
2025-04-11
Company data provided by crunchbase