Machine Learning Infrastructure Engineer Intern

About the role#

Plus is seeking a Machine Learning Infrastructure Engineer Intern to focus on optimizing large-scale model training pipelines. This role involves identifying computational bottlenecks and developing high-performance solutions to accelerate Bird's Eye View (BEV) model training. You will work with advanced profiling tools and explore the integration of Large Language Models (LLMs) to improve code generation and kernel optimization.

What you'll do#

• Profile and analyze BEV model training pipelines to identify computational and memory bottlenecks.
• Design and implement high-performance custom compute kernels using CUDA, Triton, or C++.
• Explore and integrate LLMs to assist in generating optimized code and refining kernel logic.
• Build systems to automate performance profiling using NVIDIA Nsight and the PyTorch Profiler.
• Analyze profiling data from human and LLM-assisted workflows to maximize GPU utilization and reduce training times.

What you'll need#

• Strong proficiency in C++ with a solid understanding of memory management, computer architecture, and parallel processing.
• Hands-on experience with PyTorch, including custom operations, autograd, and training loops.
• Strong problem-solving skills with an interest in performance tuning, algorithmic efficiency, and low-level system optimization.
• Preferred qualifications include experience with GPU programming (CUDA/Triton), hardware profiling tools, LLM-assisted development, and knowledge of BEV models or 3D perception.
• Pursuing a degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or Mathematics.

Location & details#

• Location: Santa Clara, California
• Term: Summer 2026
• Modality: On-site
• Status: Full-time, paid internship