Research Scientist Research Assistant Professor in Artificial Intell

Job Title

Research Scientist
- Open Rank (

Working Title:

Research Assistant Professor in Artificial Intelligence)

Atlanta, GA

The Signal Lab in the School of Electrical and Computer Engineering at Georgia Tech is seeking a Research Scientist to lead and advance cutting‑edge research in Artificial Intelligence. The role will involve laboratory management, project oversight, and business development activities to name a few.

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.

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, or
• 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, or
• A Doctoral degree and four (4) years of relevant full‑time experience after completion of a Bachelor's degree.

• 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,…