Machine Learning Research Engineer

  • nuTonomy
  • Santa Monica, CA, US
  • 29/10/2018
Full time Autonomous vehicles Deep learning Engineering Machine learning Programming

Job Description

We are seeking a highly talented Machine Learning Research Engineer in Santa Monica, CA to support a variety of teams and projects.
In this role you would work closely with other researchers & engineers to build a fully-integrated autonomous driving stack. nuTonomy’s goal is to create provably safe and efficient vehicles, so we particularly value a rigorous statistical background and expertise regarding providing rigorous performance bounds.
To support your work, you will be able to use a state-of-the-art scalable computing, simulation, and testing environment, as well as a vast database of well annotated data from nuTonomy’s fleet of autonomous vehicles. You will work together with an awesome group of motivated colleagues, both industry professionals as well as leading researchers from academia, who like to approach problems with both creativity and rigor, to push beyond the state of the art.

Job responsibilities

  • Analyze logs to identify problem areas and improvement opportunities.
  • Mine driving logs for anomalies & corner cases.
  • Develop an ‘active learning’ feedback loop for our DL / ML systems.
  • Define system documentation, metrics, measurements.

Core skills

  • Deep understanding of common Machine Learning and Deep Learning algorithms.
  • Practical experience in data science, statistics, and analysis of large data sets.
  • Fluency in in a modern programming language, such as C++ and/or Python.
  • Phd or Ms in Computer Science or similar preferred.

Desired skills

  • Experience using data modeling tools such as Pandas or Hadoop.
  • Familiarity with autonomous robotics and vehicle systems.
  • Relevant industry experience.
  • Proven track record of publications in relevant conferences (CVPR, ICML, NIPS, ICCV, ICLR…)
  • Familiarity with C++, CUDA, Git, CMake, continuous integration tools and the agile development process.