Tesla AI Machine Learning Department- 2022 AfroTech World Application @ Tesla - Palo Alto, CA

Job Overview

a month ago

Tesla AI Machine Learning Department- 2022 AfroTech World Application

Tesla - Palo Alto, CA

Our Company


Tesla is accelerating the world’s transition to sustainable energy. We design, manufacture, sell and service the world’s best solar technology, energy storage systems, and electric vehicles, providing customers the opportunity to generate, store and consume energy entirely sustainably.


Tesla is committed to hiring and developing top talent from around the world for any given discipline. Based in California, Tesla’s workforce spans across four continents. We work to build an inclusive environment in which all people, regardless of gender, race, religion, or background, can come to do their best work.


Our world-class teams operate with a non-conventional philosophy of inter-disciplinary collaboration. Each member of the team is expected to challenge and to be challenged, to create, and to innovate. We’re tackling the world’s most difficult and important problems—and we wouldn’t succeed without our shared passion for making the world a better place.


As a member of the Autopilot AI team you will design, implement, and optimize deep learning dataset generation, training, and evaluation tools and infrastructure to advance the state of the art in perception and control for autonomous driving. A typical day to day includes implementing data generation pipelines, developing tools for data exploration, debugging, evaluation, deployment of deep learning models.


Responsibilities


  • Design and implement large-scale data processing pipelines that handle a diverse set of Autopilot related data such as images, sensor inputs, and human labels.
  • Design and implement tools, tests, metrics, and dashboards to accelerate the development cycle of our model training.
  • Work on the tools and infrastructure of whatever the AI team needs to be effective.
  • Write robust Python software code in our machine learning training repository while applying best software practices to support machine learning scientists in tasks such as fetching training data, preprocessing it, and orchestrating the training runs.


Requirements


  • Strong software engineering practices, understanding how to write readable and well maintainable code. Very comfortable with Python programming, debugging/profiling, and version control.
  • We train neural networks on a cluster in large-scale distributed settings. An ideal candidate is very comfortable in cluster environments and understands the related computer systems concepts (CPU/GPU interactions/transfers, latency/throughput bottlenecks during training of neural networks, CUDA, pipelining/multiprocessing, etc).
  • We are at the cutting edge of deep learning applications. The ideal candidate has a strong understanding of the under the hood fundamentals of deep learning (layer details, backpropagation, etc).
  • Experience with PyTorch, or at least another major deep learning framework such as TensorFlow, MXNet.
  • Some experience with data science tools including Python scripting, numpy, scipy, matplotlib, scikit-learn, jupyter notebooks, bash scripting, Linux environment.
  • Optional: Devops experience, in particular dealing with clusters of training nodes, and filesystems for very large amount of training data.
  • Optional: the ability to read and implement related academic literature and experience in applying state of the art deep learning models to computer vision (e.g. segmentation, detection) or a closely related area (speech, NLP).

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