PhD Software Engineering Intern, Decision Intelligence

Nvidia

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Work type
On-site
Location
Santa Clara, CA
Employment
Full-time
Posted
158 days ago
Freshness
Confirmed live today

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Similar $178k
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About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · PhD Software Engineering Intern, Decision Intelligence

The PhD Software Engineering Intern, Decision Intelligence - Fall 2026 will join the cuOpt team to help build a GPU-accelerated open-source platform for decision-making systems. In this role, you will prototype and develop parallel algorithms for decision optimization problems while performing tuning, optimization, and benchmarking of large-scale parallel numerical software. You will collaborate with team members to understand software use cases and requirements. The position requires excellent parallel C++ and CUDA programming skills, a deep understanding of algorithms, numerical methods, and operations research fundamentals. You must be proficient in mathematical programming, including linear, quadratic, and mixed-integer models, or heuristics like genetic algorithms. Candidates should also possess knowledge of hardware architecture, performance optimization, and scripting languages like Python to solve complex decision intelligence problems.

What you'll do

  • Prototype and develop parallel algorithms for decision optimization problems.
  • Perform tuning, optimization, and benchmarking of large-scale parallel numerical software.
  • Translate software use cases and requirements into technical specifications.
  • Implement mathematical programming techniques including linear, quadratic, and mixed-integer models.
  • Apply heuristics such as genetic algorithms and large neighborhood search to optimization problems.
  • Lead independent development efforts for GPU-accelerated open-source platforms.
  • Optimize software performance across CPU, GPU, memory, and storage architectures.

What we're looking for

  • Pursuing a PhD degree in Computer Science or a related field.
  • Excellent parallel C++ programming skills with familiarity in CUDA programming.
  • Deep understanding of algorithms and numerical methods.
  • Fundamentals in operations research and optimization.
  • Mathematical programming skills in linear, quadratic, mixed-integer, or heuristics like genetic algorithms.
  • Ability to work independently and lead your own development effort.
  • Experience in algorithmic discovery via autoresearch agents and automated code evolution (preferred).
  • Track record of relevant open-source contributions in optimization, machine learning, or GPU programming (preferred).

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