On our Map Semantics team, you will have the opportunity to work with world-class machine learning (ML) engineers, whose mission is to make self-driving vehicles a reality and to create a positive social impact. The team develops ML models that detect fixed, semantic objects in multi-modal data, enabling mapping and real-time localization. These objects include lane lines, stoplights, traffic signs and other structures in the built environment. We are looking for proven technical experts who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You'll Be Doing:

Define and execute semantic scene mapping projects that improve our self-driving vehicles capability to efficiently map roadways and localize itself using autonomous vehicle and remote sensing data
Develop machine learning models to reliably and efficiently detect the built environment using single or multi-modal sensor data including vision, LIDAR, and RADAR
Productionize and deploy solutions onto autonomous vehicle fleets
Collaborate with localization, mapping and perception teams to improve your products on-road performance

What We're Looking for:

Masters or Ph.D. in Computer Science or a related technical field or equivalent industry experience
7+ years of professional software engineering experience.
Experience with real-time object and scene element detection
Experience with deep learning frameworks such as TensorFlow or PyTorch
Fluency in Python, including standard scientific computing libraries
Proven track record of designing, developing and deploying ML solutions for autonomous vehicles or robotics
Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
Extensive experience in metrics design and metrics driven technology development
Excellent communication and interpersonal skills
Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, WACV, AAAI, ICL, etc.)

Bonus Points:

Familiarity with multi-view geometry, factor graph optimization / bundle adjustment
Experience with embedded systems and real-time optimization, especially in the autonomous driving industry
Remote sensing experience including geospatial coordinate frames, object detection, RPC camera models
Experience with change detection and updating maps based on newly collected data
Experience with un/self/semi/weakly-supervised learning techniques
Strong programming skills in C++

Staff Software Engineer