NVIDIA’s Agentic Memory team is seeking a Senior Software Engineer with experience using, developing and researching agents in a variety of applications. The role involves designing evaluation methodologies, building data pipelines, and conducting experiments to enhance agentic memory systems.
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
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
- Candidates with a Master's, Ph.D. or equivalent experience in retrieval or multimodal research are preferred
- A history of mentoring junior engineers and interns is a plus
- A track record of publication in leading conferences like CVPR, ICLR, ICCV, ECCV, KDD, etc