Senior Software Engineer - Agentic Memory

NVIDIA•Us, CA

1d•Remote

About The Position

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. At NVIDIA, we’re exploring the frontier of what agents are capable of and constantly pushing to improve them. Our work builds upon the efforts of dozens of teams in the NVIDIA ecosystem and focuses on measuring and improving the performance of agentic memory. Come be a part of our world-class team building the future of agents. GPU computing is the most productive and pervasive platform for deep learning and AI. It begins with the most advanced GPUs and the systems and software we build on top of them. We integrate and optimize every deep learning framework. We work with most major technology providers and support a broad range of Fortune 500 companies in their machine and deep learning needs. With deep learning, we can teach AI to do almost anything. New internet services, like Google Assistant, have learned speech from sound and provide a more natural way to access information. Self-driving cars use deep learning to recognize the space they inhabit, the lanes they drive in, and the objects to avoid. In healthcare, neural networks trained with millions of medical images can find clues in MRIs that until now could only be found through invasive biopsies. With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We work with some of the most forward-thinking, versatile people in the world, and our engineering teams are growing fast in some of the most impactful fields of our generation: Artificial Intelligence, Data Science, Deep Learning. If you're a creative engineer who enjoys autonomy and shares our passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until April 12, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

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.

Nice To Haves

A history of mentoring junior engineers and interns is a plus.
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.

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.