5 trainee development program jobs found

Requisition Id 16889 Overview: The National Center for Computational Sciences (NCCS) provides state-of-the-art computational and data science infrastructure for technical and scientific professionals to accelerate scientific discovery and engineering advances across a broad range of disciplines. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division also hosts the Oak Ridge Leadership Computing Facility (OLCF), a Department of Energy Office of Science User Facility. The OLCF has the charge to develop and apply transformational computational science capabilities in support of dramatic advances in our understanding of the physical world and using that knowledge to address the most pressing national and international concerns. It delivers leadership- class computing for science and engineering; focuses on grand-challenge science and engineering applications; procures largest-scale computer systems (beyond typical vendor design points) and...

Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders, soldiers in battlefield scenarios, and beyond. About the team: The Skydio Training team is transforming how pilots, technicians, and operators learn. As our programs continue to evolve beyond traditional classroom instruction into immersive, simulation-driven learning experiences, we are building the next generation of technical education for autonomous flight. The Training Content team partners closely with instructors, curriculum developers, product teams, software engineers, simulation developers, and subject matter experts to create learning experiences that...

Requisition Id 16413 Overview: The Analytics and AI methods at Scale (AAIMS) group in the National Center for Computational Science (NCCS) is hiring Senior Research Scientist to push the frontier of AI for science such as: scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models on leadership-class supercomputers. You'll help design, train, and evaluate AI systems that plan, reason, and take actions to accelerate discovery across domains (materials, chemistry, climate, fusion, biology, and more). NCCS operates the Frontier exascale supercomputer and world-class data facilities. This role sits at the intersection of AI at scale and HPC, giving you unmatched resources to prototype new ideas, run large ablations, and translate methods into scientific impact. Examples of Focus Areas: Agentic AI for Science: Autonomous and tool-using agents for experiment design, simulation steering, data collection, and...

Are you a cybersecurity and/or AI researcher who enjoys a challenge? Are you excited about pioneering new research areas that will impact academia, industry, and national security? If so, we want you for our team, where you'll collaborate to deliver high-quality results in the emerging area of AI security. The CERT Division of the Software Engineering Institute (SEI) is seeking applicants for the AI Security Researcher role. Originally created in response to one of the first computer viruses -- the Morris worm - in 1988, CERT has remained a leader in cybersecurity research, improving the robustness of software systems, and in responding to sophisticated cybersecurity threats. Ensuring the robustness and security of AI systems is the next big challenge on the horizon, and we are seeking life-long learners in the fields of cybersecurity, AI/ML, or related areas, who are willing to cross-train to address AI Security. As part of the Threat Analysis Directorate, you will join a group...

About the Company Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we've built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost ( 7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb) and pretraining with domain-specific data (The Finetuner's...