Lead AI Systems Engineer

2 weeks ago

Santa Clara, California, United States NVIDIA Full time

NVIDIA is on the lookout for a skilled Lead AI Systems Engineer to become a vital part of our Autonomous Vehicles division. In this position, you will leverage artificial intelligence to enhance Autonomous Vehicle perception, contributing to the development of our cutting-edge autonomous driving technology. We seek an innovative and inquisitive engineer who is both proactive and meticulous, with a passion for uncovering solutions to complex challenges. NVIDIA boasts some of the most visionary and dedicated professionals globally. If this resonates with you, we would love to connect.

Key Responsibilities:

  • Optimizing our deep neural network (DNN) training framework: enhancing speed, scalability, and resource efficiency.
  • Architecting our training infrastructure to support simultaneous usage by multiple engineers across various tasks.
  • Curating datasets for training: constructing a horizontally scalable data preparation pipeline that is user-friendly and minimizes training delays.
  • Developing a high-throughput cloud inference pipeline for evaluation and key performance indicator (KPI) assessment.
  • Streamlining processes to facilitate the creation of verified, deployable artifacts from annotated datasets.
  • Creating tools for analysis and visualization to gain insights into performance and areas for improvement.
  • Aiming for optimal efficiency in training, data preparation, and cloud inference.
  • Collaborating closely with platform and perception DNN engineers, merging expertise in large-scale machine learning systems with in-depth knowledge of perception DNNs.

Qualifications:

  • Master’s or Doctorate in computer science or a related field, or equivalent experience.
  • Minimum of 3 years of relevant industry experience.
  • Proficiency in contemporary machine learning frameworks such as PyTorch.
  • Strong programming skills in C++, Python, and/or CUDA.
  • A commitment to software development excellence and code quality, adhering to the latest standards and practices, writing unit tests and benchmarks, and consistently improving code quality.
  • A passion for optimization: skilled in writing efficient code, from high-level machine learning algorithms to low-level hardware utilization.
  • Strong communication and collaboration skills: ability to work effectively within a large ecosystem, serving both as a client and provider to other teams.

Preferred Qualifications:

  • Publications in the field of efficient machine learning (accelerating training and inference).
  • Experience in developing large-scale machine learning pipelines, particularly for autonomous vehicles.
  • Significant contributions to leading open-source projects in related areas.

The field of perception for autonomous technologies presents one of the most exhilarating and demanding challenges today. Machine Learning plays a crucial role, but to excel in this domain, we must master the fundamentals. Join the Perception ML Foundation team, where we integrate expertise in machine learning, high-performance computing, and cloud computing to establish the perception ML 'factory.' This factory streamlines the generation of perception ML models, making it efficient, scalable, and user-friendly. It encompasses essential ML workflows: data preparation, DNN training, production optimization, and extensive cloud inference and evaluation.

We believe that creating this high-throughput factory necessitates diverse, interdisciplinary thinking and expertise: understanding modern perception architectures, machine learning optimization techniques, large-scale software systems, high-performance computing, and the hardware driving accelerated cloud computing, as well as MLOps and microservices. We refer to all these skills as ML foundation engineering. If this aligns with your expertise and passion, you may be the perfect fit for our team at NVIDIA.

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