Senior System Software Engineer, ML and Vector Search

NVIDIA AI; Santa Clara (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Equity

Job summary

NVIDIA AI in Santa Clara, CA is seeking an experienced software engineer to design and implement optimized GPU algorithms for large-scale vector search and ML workloads. You will drive performance analysis and contribute to open-source libraries.

The role requires a CS degree and 8+ years of C++ experience, plus mastery of CUDA, Python, and parallel programming. You will collaborate across teams to push the limits of GPU acceleration and performance.

Qualifications

• Bachelor's degree in CS or related field.
• 8+ years of experience in C++ or similar languages.
• Proficiency in ML concepts, parallel programming frameworks, and strong analytical problem-solving skills.

Responsibilities

• Design and implement optimized GPU algorithms for large-scale vector search, databases, and ML workloads.
• Drive performance analysis and optimization across GPU pipelines.
• Contribute to open-source libraries like cuML, cuVS, and RAFT.

Skills

C++

CUDA

Python

ML basics

Vector search

GPU programming

Algorithm optimization

Performance analysis

Parallel programming

Distributed systems

Open source

Education

Bachelor's degree in Computer Science or related field

Job description

The role involves designing and implementing optimized GPU algorithms for large-scale vector search, databases, and machine learning. You will drive performance analysis and contribute to open-source libraries like cuML, cuVS, and RAFT.

Requirements: Candidates need a degree in Computer Science or a related field and 8+ years of experience in C++ or similar languages. Proficiency in ML concepts, parallel programming frameworks, and strong analytical problem-solving skills are required.

Key Skills: C++, CUDA, Python, Machine Learning, Vector Search, GPU Programming, Algorithm Optimization, Performance Analysis, Clustering, Dimensionality Reduction, Distributed Systems, Parallel Programming, Data Structures, Benchmarking, Open Source Contribution

Benefits: Equity