1 day ago
Base Salary
$184k - $288k/yr
Responsibilities
- Analyze, design, and implement optimized GPU algorithms for large-scale vector search, databases, and machine learning.
- Drive performance analysis, benchmarking, and optimization of associated libraries.
- Develop and improve machine learning algorithms for clustering, visualization, and related workloads.
- Implement solutions in C++, CUDA, and Python.
- Collaborate with multifunctional teams to understand requirements and improve solutions.
- Contribute to open-source projects including cuML, cuVS, and RAFT.
- Research and explore novel tuned algorithms for vector preprocessing, indexing, and search.
Requirements
- BS, MS, or PhD in Computer Science, Data Science, AI, Applied Mathematics, or a related field, or equivalent experience.
- 8+ years of experience programming in C++, or ability to learn C++ from a similar language such as C, Rust, or Java.
- Experience with machine learning concepts, ML algorithm development, and applying ML to solve problems.
- Strong analytical problem-solving, algorithm, and mathematics fundamentals.
- Strong software development skills, including programming, debugging, performance analysis, and test design.
- Familiarity with at least one parallel programming or concurrency framework, such as CUDA, OpenMP, OpenACC, Java concurrency, or pthreads.
- Ability to work independently and manage development efforts, with strong communication and documentation habits.
- Experience with distributed algorithms and distributed systems such as HPC or cloud environments is a plus.
- Familiarity with vector databases and nearest-neighbor algorithms, including Milvus, Pinecone, LanceDB, graph indexes, or IVF indexes, is a plus.
- Background in clustering, dimensionality reduction, probability, formal methods, or applied research is a plus.
- GPU programming experience is a plus.
Benefits
- Competitive salary package, equity, and benefits.
- Applications will be accepted at least until September 12, 2026.
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.