Research Engineer, Self Driving
We're changing the way people think about transportation. Not that long ago we were just an app to request premium black cars in a few metropolitan areas. Now we're a part of the logistical fabric of more than 600 cities around the world. Whether it's a ride, a sandwich, or a package, we use technology to give people what they want, when they want it.
For the people who drive with Uber, our app represents a flexible new way to earn money. For cities, we help strengthen local economies, improve access to transportation, and make streets safer.
And that's just what we're doing today. We're thinking about the future, too. With teams working on autonomous trucking and self-driving cars, we're in for the long haul. We're reimagining how people and things move from one place to the next.
About the Role
You will participate in the unique effort of bringing innovative state-of-the-art deep-learning models for self-driving into production, and onto autonomous vehicles. You will collaborate closely with a team of highly skilled researchers and engineers, tackling an array of challenges related to applying machine learning to self-driving vehicles. You will work on a variety of research engineering tasks related to algorithms for detection & perception, prediction, motion planning & automated map production, to name a few.
What You'll Do / What You'll Need / Bonus Points / About the Team
What You'll Do
- Develop in-depth understanding of deep learning models and algorithms and contribute to optimizing their training protocols, as well as test-time performance, runtime, memory footprint, and power consumption.
- Design and implement tools for automated model tuning and hyperparameter optimization, as well as experiment analysis
- Collaborate and communicate closely with researchers to identify, propose and build infrastructure, data and computation pipelines, data storage strategy, common libraries and useful tools needed to optimize research and development of deep-learning models
- Research, validate and incorporate emerging machine learning and research infrastructures, tools, and technologies
What You'll Need
- Minimum 4 years experience building production level software systems, preferably with Python and C++ (candidates not meeting this requirement but excel in other competencies will be considered)
- Expertise in performance evaluation and optimization of deep learning or computational science algorithms, particularly using GPUs and distributed computing
- Experience with parameter and architecture tuning of deep learning algorithms
- Solid knowledge of Python and C++ internals, including scientific computing libraries
- Demonstrable track-record of learning and deep-diving as needed into complex existing and new technologies
- Intense sense of ownership, initiative-taking, and a can-do attitude
- Great attention to detail and a data-driven approach to problem solving
- Team-player with a strong collaboration and communication skills, who responds positively to feedback
- Expert level knowledge of one or more of the following: TensorFlow, PyChram, CUDA, cuDNN, OpenCL
- Familiarity with considerations related to sensor data (RGB, LiDAR) such as calibration, data capturing, noise sources, transformations, etc.
- Familiarity with standard web software frameworks for implementing internal research tools
About the Team
At the Advanced Technologies Group (ATG), we are building technologies that will transform the way the world moves. Our teams are building self-driving systems that will one day move people and things around more safely, efficiently, and cost effectively. To achieve this goal, we are creating the most advanced technologies that we can dream up.
Working alongside world-renowned researchers who are developing computer vision deep-learning algorithms for various self-driving tasks, our team delivers these algorithms to the real world and bring them into production. We are provided the rare opportunity to create a ground-breaking product changing the future of transportation globally, using the most advanced and exciting technologies, tools, and techniques.
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