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++
