3 days ago
Base Salary
$152k - $288k/yr
Responsibilities
- Design and implement GPU-accelerated pipelines processing multi-terabyte and petabyte-scale cyber, network, and industry datasets.
- Develop proof-of-concept technologies and discussions addressing accelerated and AI compute workloads for customer problems.
- Serve as a technical lead and liaison among NVIDIA engineering, product teams, and OEM partners.
- Guide agentic AI workflows involving semantic search, retrieval-augmented generation, and Graph Neural Network applications for threat detection.
- Translate AI and cybersecurity research into deployable architectures for enterprise and government customers.
Requirements
- Bachelor’s, master’s, or doctoral degree in Computer Science, AI Engineering, Data Science, or a related field, or equivalent experience.
- At least five years of experience in technology-focused roles such as Solutions Architecture, Data Science, or AI Research.
- Expertise in supervised and unsupervised machine learning, deep learning, and statistics applied to loosely structured data and security logs.
- Strong coding, debugging, and pipeline development skills using Python, C/C++, Bash, and Linux utilities.
- Hands-on experience with big data, AI frameworks, GPU acceleration, Spark, and distributed computing environments.
- Strong communication, presentation, analytical, problem-solving, and multitasking skills.
- Preferred experience with NVIDIA open-source projects and tools such as Morpheus, RAPIDS, NVIDIA DPU DOCA, or similar accelerated-compute libraries.
- Preferred experience integrating AI workloads with Splunk, data pipeline architectures, or AI security protection ecosystems.
- Preferred experience in technical leadership or principal investigator roles on large-scale or secure enterprise projects.
- Preferred background in agentic AI, LLM deployment, ingestion and retrieval technologies, and public speaking at technical events.
Benefits
- Competitive base salary and comprehensive benefits package.
- Eligibility for equity and benefits.
- Applications accepted at least until November 13, 2026.
Tech Stack
Categories
Solutions Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.