Mobileye
Mobileye
Mobileye izstrādā progresīvas autovadītāja palīdzības sistēmas un autonomās braukšanas tehnoloģijas automobiļu nozarei. Uzņēmums apvieno datorredzi, mākslīgo intelektu, paša izstrādātu aparatūru un programmatūru, lai atbalstītu transportlīdzekļu drošību risinājumos, kas aptver gan autovadītāja palīdzību, gan autonomu braukšanu. Uzņēmuma sistēmas ir ieviestas vairāk nekā 190 miljonos transportlīdzekļu, apliecinot Mobileye nozīmi uz redzi balstītu automobiļu tehnoloģiju ieviešanā plaša mēroga ražošanā.

Senior Deep Learning Researcher, Autonomous Vehicles

Research and develop deep learning systems for Mobileye’s autonomous vehicles, including large-scale neural networks built for its EyeQ chip. Improve model performance and bring research into production.

Apraksts

  • Develop and train deep learning models optimized for Mobileye’s custom EyeQ chip.
  • Create large-scale, multi-task neural networks for Mobileye’s autonomous driving system.
  • Solve end-to-end deep learning problems and deploy solutions in real-world systems.
  • Design new model architectures and use advanced training methods.
  • Optimize model performance within strict constraints.
  • Partner with software and hardware teams to turn research into production systems.
  • Help shape the core neural network architecture used in Mobileye’s flagship autonomous vehicle products.

Prasības

  • PhD in Computer Science or a related field; exceptional candidates with an MSc may be considered.
  • At least 4 years of hands-on experience developing deep learning algorithms in Python.
  • Experience building end-to-end deep learning pipelines covering data preparation, training, evaluation, and deployment.
  • Proficiency with at least one deep learning framework, such as TensorFlow or PyTorch.
  • Strong problem-solving skills and a research-focused approach.
  • Industry experience in deep learning or software development is an advantage.
  • Familiarity with hardware-aware model optimization is an advantage.
  • Experience with cloud platforms such as AWS, Docker, and Linux environments is an advantage.
  • Publications or contributions in deep learning, neural architecture search, knowledge distillation, or multi-task learning are an advantage.

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