Principal Deep Learning Optimization Engineer

San Francisco, California
US$250000 - US$270000 per annum

Principal Deep Learning Engineer

$250,000 - $270,000

SAN FRANCISCO

Do you want to work in the autonomous vehicle space? Do you want to be a part of launching self-driving vehicles at scale? Are you interested in a company that has raised billions and is backed by other well-known companies? Do you want to contribute to a mission that will help reduce carbon emission, save lives, and helps relieve crowded urban environments? If you have experience optimizing Deep Learning models and are familiar with model quantization and/or model compression, apply now!

THE COMPANY:

This company is very advanced in the autonomous vehicle space! This company is working towards launching self-driving vehicle at scale with a mission to help reduce carbon emission pollution, save lives, and help make cities less crowded.

THE ROLE: PRINCIPAL DEEP LEARNING ENGINEER

As a Principal Deep Learning Engineer, you will be optimizing Deep Learning models, building algorithms that optimize models, and interfacing with all different teams including computer vision, perception, and platform to understand requirements and constraints. You will also be able to do research as well (i.e. reading publications and learning new methods).

Specifically, you can expect to be involved in the following:

  • Optimize all deep learning models before deployment phase in the cars
  • Build algorithms that optimize models
  • Interface with all different teams including Computer Vision, Perception, and Platform to understand requirements and constraints
  • Read publications and learn new methods
  • Research and prototype different model optimization techniques and algorithms

YOUR SKILLS AND EXPERIENCE:

A successful Principal Deep Learning Engineer will have the following:

  • Experience with one of the following: Neural Net Compression, Quantization (Pruning, Factorization, Knowledge Distillation, etc.), or Neural Architecture Search (NAS)
  • Has developed models in Deep Learning, ideally Computer Vision
  • Has developed production level code in Python or C++
  • Experience with Deep Learning frameworks including Tensorflow and PyTorch
  • Ability to read research papers and implement it

Even better if you have:

  • GPUs experience
  • Distributed computing experience
  • Numerical optimization experience
  • Compiler experience

THE BENEFITS:

  • $ 250,000 - $270,000

HOW TO APPLY:

Please register your interest by sending your CV to Kayla Nague via the Apply link on this page.

KEYWORDS: Machine Learning, Data Science, Python, Computer Science, Engineering, Artificial Intelligence, Algorithm Development, Deep Learning, TensorFlow, PyTorch, Neural Net Compression, Quantization, Pruning, Factorization, Knowledge Distillation, Computer Vision, Neural Architecture Search (NAS), Optimization, GPU, Distributed Computing, Numerical Optimization, Compiler

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101310/KN
San Francisco, California
US$250000 - US$270000 per annum
  1. Permanent
  2. Data science

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