Research Scientist

Machine Learning, Planner/Behavior Prediction

Confirmed live in the last 24 hours

Locations

Mountain View, CA, USA

Experience Level

Entry

Junior

Mid

Senior

Expert

Desired Skills

Data Structures & Algorithms

C/C++/C#

Pytorch

Tensorflow

Python

Requirements

Post Graduate degree (MS or PhD) in Computer Science, Robotics, Electrical Engineering or Mathematics with specialization in Machine Learning, Reinforcement Learning or Robotics
Experience solving problems using Machine Learning with Tensorflow/PyTorch or equivalent tools
Ability to collaborate within and across teams
Strong experience programming in C++ or Python with robust and efficient code
Experience specifically with applying Machine Learning to solve motion planning or related robotics problems
Solid understanding of machine learning, deep learning algorithms and computational complexity
Published and/or presented papers at ICML, NIPS, KDD, CVPR, ICCV, WWW or similar top-tier conferences and events
Experience with Deep Learning Models (e.g. RNN/LSTM, CNN, VAE, GAN, etc.) using Machine Learning with Tensorflow/PyTorch or equivalent tools

Responsibilities

Design data-driven algorithms to improve the safety, generalization and reliability of self-driving algorithms, including: framing the open-ended real-world driving problems into well-defined ML problems; building training / evaluation pipelines to solve the problem, and landing them in real world driving
Gracefully handling many complex situations involving social aspects (merging, negotiating narrow roads, etc), while dealing with noisy, uncertain, and incomplete information
Conduct the research of ML planning and decision-making learning in the autonomous driving area. Write and publish papers in the relevant top-tier AI conferences
Collaborate with other teams, including the ML infrastructure, perception and systems engineering teams

Responsibilities:

Design data-driven algorithms to improve the safety, generalization and reliability of self-driving algorithms, including: framing the open-ended real-world driving problems into well-defined ML problems; building training / evaluation pipelines to solve the problem, and landing them in real world driving.
Gracefully handling many complex situations involving social aspects (merging, negotiating narrow roads, etc), while dealing with noisy, uncertain, and incomplete information.
Conduct the research of ML planning and decision-making learning in the autonomous driving area. Write and publish papers in the relevant top-tier AI conferences.
Collaborate with other teams, including the ML infrastructure, perception and systems engineering teams.

Qualifications:

Post Graduate degree (MS or PhD) in Computer Science, Robotics, Electrical Engineering or Mathematics with specialization in Machine Learning, Reinforcement Learning or Robotics
Experience solving problems using Machine Learning with Tensorflow/PyTorch or equivalent tools
Ability to collaborate within and across teams
Strong experience programming in C++ or Python with robust and efficient code

Preferred:

Experience specifically with applying Machine Learning to solve motion planning or related robotics problems
Solid understanding of machine learning, deep learning algorithms and computational complexity.
Published and/or presented papers at ICML, NIPS, KDD, CVPR, ICCV, WWW or similar top-tier conferences and events.
Experience with Deep Learning Models (e.g. RNN/LSTM, CNN, VAE, GAN, etc.) using Machine Learning with Tensorflow/PyTorch or equivalent tools.

The expected salary range is $129,189 to $296,400 + bonus + equity + benefits. Actual starting pay will be based on job-related factors, including exact work location, experience, training, and skill level, so may be higher or lower than what is shown on this posting. This job may be also eligible for additional discretionary bonuses and equities.

About the Company:

Didi Chuxing (“DiDi”) is the world’s leading mobile transportation platform. We’re committed to working with communities and partners to solve the world’s transportation, environmental, and employment challenges by using big data-driven deep-learning algorithms that optimize resource allocation.

Didi Chuxing’s Autonomous-Driving team was established in 2016 and has grown to a comprehensive research and development organization covering HD mapping, perception, behavior prediction, planning and control, infrastructure and simulation, labeling, hardware, mechanical, problem diagnosis, vehicle modifications, connected car, and security, among others. We’re developing and testing self-driving vehicles in China and the United States.

In August 2019, DiDi upgraded its autonomous driving unit to an independent company to focus on R&D, product application, and business development related to self-driving technologies. The new company will integrate the resources and technology of DiDi’s platform, continue to increase investment in R&D, and deepen collaboration with auto industry partners.

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10,001+ employees

Website

Mobile transportation platform

Company Overview

World's leading mobile transportation platform