Machine Learning Infrastructure Engineer Intern

Santa Clara, California, United StatesOnsiteInternshipJunior / Entry-levelPosted 1 month agoVisa sponsorship available

Is this role right for you?

Upload your resume and get a skill-by-skill breakdown — see exactly where you match, where you're close, and what to highlight. Not a mystery percentage.

Get a tailored resume highlighting what this role needs.

Role summary

PlusAI is seeking a Machine Learning Infrastructure Engineer Intern to help optimize AI-based virtual driver software for autonomous trucks. This hybrid role involves identifying training bottlenecks in Bird's Eye View (BEV) model training pipelines, developing custom kernels using CUDA, Triton, or C++, and leveraging LLMs for code generation and optimization. The intern will automate profiling workflows using tools like NVIDIA Nsight and PyTorch Profiler, and continuously tune performance to maximize GPU utilization. The ideal candidate has strong systems programming skills in C++, hands-on experience with PyTorch, and a performance-oriented mindset.

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

Responsibilities:

Identify Training Bottlenecks: Profile and analyze Bird's Eye View (BEV) model training pipelines to pinpoint computational and memory bottlenecks.

Develop Custom Kernels: Design and implement high-performance custom compute kernels using CUDA, Triton, or C++ to accelerate the model training process.

Leverage LLMs for Optimization: Explore and integrate Large Language Models (LLMs) to assist in generating high-performance code and optimizing kernel logic.

Automate Profiling Workflows: Build systems to automate performance profiling and analysis using tools like NVIDIA Nsight and the PyTorch Profiler.

Iterative Performance Tuning: Continuously analyze profiling data generated by both human and LLM-assisted workflows to maximize GPU utilization and reduce training times.

Required Skills:

Systems Programming: Strong proficiency in C++ and a solid understanding of memory management, computer architecture, and parallel processing principles.

Deep Learning Frameworks: Hands-on experience with PyTorch, specifically understanding custom operations, autograd, and training loops.

Performance-Oriented Mindset: Strong problem-solving skills with a deep interest in performance tuning, algorithmic efficiency, and low-level system optimization.

Preferred Skills:

GPU Programming Experience: Practical experience writing and optimizing custom GPU kernels using CUDA or OpenAI Triton.

Hardware Profiling Tools: Familiarity with hardware and software profiling tools, particularly NVIDIA Nsight (Systems/Compute) and the PyTorch Profiler.

LLM for Code Generation: Experience using or prompting LLMs for code writing, refactoring, or exploring AI-assisted software development workflows.

Autonomous Vehicle Perception: A foundational understanding of Bird's Eye View (BEV) models, 3D perception, or spatial transformers used in autonomous driving.

Your opportunities joining PlusAI

Work, learn and grow in a highly future-oriented, innovative and dynamic field.

Wide range of opportunities for personal and professional development.

Catered free lunch, unlimited snacks and beverages.

Highly competitive salary and benefits package, including 401(k) plan.

Ready to apply?

You'll be redirected to PlusAI's application page.

Is this role right for you?

Role summary

Similar roles