Software Engineer, Generalist, AI Inference: Tesla

The team is focused on productionizing machine learning models by training and deploying large neural networks for efficient inference on compute-constrained edge devices. As a multi-disciplinary engineer, you will work at the intersection of machine learning and systems to build the AI frameworks and infrastructure for all neural networks that run on Autopilot and Optimus.

Key Responsibilities
Build robust AI frameworks to lower neural networks to edge devices.

Develop AI infrastructure to train and fine-tune networks on large GPU clusters for Autopilot and Optimus.

Deploy state-of-the-art neural networks on heterogeneous compute, including Tesla's in-house AI ASIC, with a focus on maximizing performance and minimizing latency.

Collaborate with AI scientists and compiler engineers to effectively compress large models.

Design and implement custom GPU kernels (CUDA / OpenCL) for efficient training and post-processing.

Required Skills & Qualifications
Proficiency in Python and C++, including modern C++ (14/17/20).

Proficiency with PyTorch or another machine learning framework.

Experience with training and deploying neural networks for real-world AI applications.

Proficiency with computer systems and computer architecture.

Experience with CUDA.