Senior/Staff Perception Machine Learning Engineer - 3D Tracking
Zoox
Software Engineering
Foster City, CA, USA
Posted on Oct 24, 2023
Zoox is looking for a software engineer to join our Perception team and help us build novel architectures for classifying and understanding the complex and dynamic environments in our cities. You will be part of a dynamic team with diverse backgrounds from software engineering, machine learning, probability theory and state estimation.
In this role, you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms. We are creating new algorithms for segmentation, tracking, classification, and high-level scene understanding, and you could work on any (or all!) of these components.
In this role, you will...
- Contribute to the ongoing development of new architecture based on new, state of the art ML research
- Investigate, prototype and train/evaluate networks for solving data association problems ie: track-detection matching, using geometric and embedded features
- Investigate, prototype and train / evaluate networks for solving recursive and / or moving window filtering / estimation problems for non-stationary non-Gaussian noise
- Investigate, prototype and train / evaluate networks for solving dynamic occupancy estimation problems with and without agent/shape assumptions
- Investigate, prototype and train / evaluate networks for solving causal / recursive multi-target multi-modal tracking problem
Qualifications
- 7+ years of experience with programming and algorithm design
- Fluency in C++ and Python
- Experience with modern computer vision techniques like Transformers
- Experience with tracking techniques like data association and state estimation
- Demonstrated ability to create realtime systems that solve difficult perception tasks
- Strong mathematical skills and understanding of probabilistic techniques
Bonus Qualifications
- Bachelor's, Master's or PhD in computer science, statistics, mathematics or related field
- Publications in your field (CVPR, ICCV, RSS, ICRA preferred)
- Experience with building perception pipelines that work with real data in rapidly changing and uncertain environments.
- Experience with realtime sensor fusion (e.g. LiDAR, camera, radar)
- Experience with data representations like pointclouds, meshes, voxel-representation, pixel-domain, etc.
- Experience with nonlinear non Gaussian multi hypotheses tracking
- Experience with weighted nonlinear least square estimation like GTSAM
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $196,000-$319,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.
Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.