Senior System Software Engineer, ML and Vector Search

Posted 13 Hours Ago
2 Locations
In-Office or Remote
184K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop optimized GPU algorithms and high-performance machine learning solutions for vector search, databases, and data processing. Responsibilities include designing, implementing, benchmarking, debugging, and optimizing C++, CUDA, and Python libraries; developing clustering and visualization algorithms; collaborating cross-functionally; and contributing to open-source projects such as cuML, cuVS, and RAFT.
Summary Generated by Built In

It’s an exciting time for NVIDIA as we expand our capabilities into the world of data science, data processing, and database acceleration. We're looking for an outstanding software engineer to apply their skills in the development of our unstructured data processing libraries, NVIDIA cuVS and cuML.

These libraries compile highly optimized C++ and CUDA algorithms and expose them to higher-level languages like Java and Python. These higher-level languages are then used directly or to accelerate other libraries and database systems. In this role, you will research, develop, benchmark, and explore novel tuned custom algorithms for accelerating vector preprocessing, indexing, and search, as well as building high-performance ML algorithms for clustering and visualization. This is a great chance to take advantage of your CUDA/C++ skills and make a huge impact across a rapidly growing industry. Vector search is an exciting new field at the intersection of database and machine learning. You’ll work closely with a team of stellar engineers redefining what’s possible.

What you will be doing:

  • 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.

  • Collaborate with a multi-functional team to understand requirements and implement or improve solutions

  • Developing and improving machine learning algorithms.

  • Implementing solutions in C++, CUDA and Python.

  • Contributing to open source projects (like cuML, cuVS, and RAFT)

What we need to see:

  • BS, MS, or PhD in Computer Science, Data Science or AI, Applied Math, or related field (or equivalent experience).

  • 8+ years of experience programming in C++ or ability to learn it, by moving from a similar language: C, Rust, Java

  • Experience with ML: ML concepts (approximation vs exact, iterative vs. closed-form), writing ML algorithms, and using ML to solve problems. 

  • Strong analytical problem-solving skills, algorithms and mathematics fundamentals.

  • Excellent software development skills: programming, debugging, performance analysis, and test design

  • Ability to work independently and manage your own development efforts.

  • Good communication and documentation habits.

  • You care deeply about robust, readable, high-performance code

  • Familiar with at least one parallel programming or concurrency framework, such as CUDA, OpenMP, OpenACC, Java concurrency, pthreads, etc

Ways to stand out from the crowd:

  • Experience developing distributed algorithms and running on distributed systems: HPC, Cloud, etc

  • Strong debugging skills, including for complex multi-language, multi-hardware systems.

  • Familiarity with vector databases and nearest-neighbor algorithms (for example, Milvus, Pinecone, LanceDB; graph and IVF indexes).

  • ML background, including clustering and dimensionality reduction; probability and formal methods; applied research

  • GPU programming is a plus, though we’re happy to teach GPU development.

With a competitive salary package and benefits, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous Systems Software Engineer who loves challenges? Do you have a genuine passion for advancing the state of Systems Analytics and Data Intelligence across a variety of industries? If so, 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 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 12, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

Skills Required

  • BS, MS, or PhD in Computer Science, Data Science or AI, Applied Mathematics, or a related field, or equivalent experience
  • 8+ years of experience programming in C++, or ability to transition from C, Rust, or Java
  • Experience with machine learning concepts, algorithms, and applications
  • Strong analytical problem-solving, algorithms, and mathematics fundamentals
  • Strong software development skills, including programming, debugging, performance analysis, and test design
  • Ability to work independently and manage development efforts
  • Good communication and documentation habits
  • Commitment to robust, readable, high-performance code
  • Familiarity with at least one parallel programming or concurrency framework, such as CUDA, OpenMP, OpenACC, Java concurrency, or pthreads
  • Experience developing distributed algorithms and running on distributed systems such as HPC or cloud environments
  • Strong debugging skills for complex multi-language, multi-hardware systems
  • Familiarity with vector databases and nearest-neighbor algorithms
  • Machine learning background including clustering, dimensionality reduction, probability, formal methods, or applied research
  • GPU programming experience

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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