Machine Learning Specialist Aurora
San Francisco, CA

Job Description

Aurora Overview

Bringing self-driving vehicles to our roads is the most transformative opportunity of our generation. Aurora is taking a fresh start with the development of self-driving technology, combining excellence in AI, rigorous engineering, and a team with decades of experience building robots that work.

Led by a team of seasoned experts, including three of the world's leaders of self-driving technology, our mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. We are designing the software and hardware to power the transportation of our future that will make our roads safer, give more people access to mobility, and reduce congestion and pollution in cities - improving the quality of life for all. The challenge in what we are endeavoring to achieve is transcendent; we are developing perhaps the world's most complex computing system and asking it to perform the task of transporting and keeping safe our most precious asset: human life.

We're looking for people who are as excited as we are to solve these complex problems and make this tremendous impact on our future, and who want to be surrounded by great people while we do it. We are searching for a Machine Learning Specialist. He/She will design and develop cutting edge algorithms that enable our self driving vehicles to adapt and improve as they gather increasing amounts of data.

Responsibilities

* Develop cutting edge machine learning algorithms for various parts of the online system including perception, planning and forecasting
* Guide the development of these algorithms from prototype to production - including training on large scale datasets, and deploying on a real time robotic platform
* Identify new areas (both online and offline) where machine learning can leverage data to enhance performance
* Design, build and maintain large scale production machine learning pipelines

Essential

* BS, MS or PhD in Robotics, Machine Learning, Computer Science, or a related field
* Strong grasp of fundamentals: linear algebra, discrete and continuous optimization, supervised and unsupervised methods, generative and discriminative methods
* Expertise in one or more focus areas: deep learning, online learning, sequential prediction, graphical models, structured prediction, sequential models, reinforcement learning, imitation learning, planning under uncertainty, bayesian inference, model compression, multi-task learning, forecasting etc.
* Proven track record of experience in relevant areas (significant industry experience and/or publication record at top venues like ICML, AISTATS, NIPS or similar)
* Excellent software skills (C++/Python) required to train and evaluate state of the art algorithms on large datasets

Desirable

* Experience with Tensorflow, Caffe and porting models to embedded platforms
* Experience applying machine learning to problems in robotics

Working at Aurora

Our work has real purpose. Delivering self-driving will improve lives around the world, expanding access to transportation, revitalizing cities, giving people more time back every day.

We're one team. We're inspired by the challenge of what we're solving and the impact our work will have on society. Our camaraderie is built on respect for our work and the fundamental belief our success will be a result of working together.

The Founding Team

Aurora has assembled the most experienced leadership team in the space. Chris Urmson helped lead Carnegie Mellon's efforts in Darpa's Grand Challenges, then was a founding member of Google's self-driving team. Sterling Anderson worked on the tech at MIT before leading Tesla's Autopilot system. Drew Bagnell, also a Carnegie Mellon alum, is a machine learning expert who helped build Uber's autonomy effort. At Aurora, these three continue to bring experts from all areas of the industry to the team. We are funded by some of Silicon Valley's best venture capital firms, including Greylock and Index Ventures.