About the job
NVIDIA’s Agentic Memory team is seeking a Senior Software Engineer with experience using, developing and researching agents in a variety of applications. You’ll join a team of researchers with deep experience in building information retrieval systems, who are now working on advancing the state of the art of agentic memory.
Responsibilities
Designing novel benchmark tasks and evaluation methodologies that measure the effectiveness of agentic memory systems including semantic, episodic, and procedural memory across multi-session and multi-turn agent trajectories.
Building and maintaining synthetic dataset generation pipelines that produce realistic, enterprise-relevant evaluation data at scale.
Designing and running experiments to understand where agent memory falls short, diagnose root causes, and inform improvements.
Developing and contributing to open-source evaluation harnesses that enable rigorous, reproducible comparison of memory system architectures.
Partnering with teams across NVIDIA who are deploying agents to understand the role of memory in a variety of applications and help integrate improvements.
Contributing to public-facing benchmarks and leaderboards that advance the state of the art in agentic memory evaluation.
Integrating our work to leverage and improve the full NVIDIA software ecosystem, working across team boundaries in the spirit of extreme codesign.
Keeping up to date with the latest developments in agentic memory across academia and industry.
Qualifications
Minimum
Master’s degree (or equivalent experience) or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or Applied Math with 12+ years of experience
Hands-on experience developing agentic systems and pipelines, with a preference for those that integrate and involve memory.
An understanding of the state of the art in retrieval research, with a focus on agentic retrieval.
Knowledge of best practices in batching, streaming, and scaling of large-scale data pipelines to support real-world applications.
Excellent Python programming skills and a strong understanding of the Python deep learning ecosystem.
An ability to share and communicate your ideas clearly through blog posts, papers, GitHub, etc.
Excellent communication and interpersonal skills are required, along with the ability to work in a dynamic, product-oriented, distributed team. A history of mentoring junior engineers and interns is a plus.
Preferred
Candidates with a Master's, Ph.D. or equivalent experience in retrieval or multimodal research are preferred, along with a track record of publication in leading conferences like CVPR, ICLR, ICCV, ECCV, KDD, etc.