I am working with a revolutionary software-based ADAS Series E startup who are on a mission to create the first consumer-vehicle self-driving system which is safe and accessible to the general public. Their technology is based on a breakthrough bottom-up approach to training their neural networks which relies on a real-time understanding of universal physics, coupled with a varied and overlapping sensor array which lends itself specifically to the system in place. This role is situated within the core Model Engineering team.
- Build, test and optimise robust L4 Deep Learning Algorithms for semantic understanding of visual scenes in front of the vehicle
- Develop metrics of evaluation to analyse and optimize real-world vehicle data
- Understand and solve non-linear 3D mathematics problems with open-ended solutions
- Place models through production, working cross-functionally with various teams such as Software, Perception and Engineering teams to fully integrate it into the vehicle
- Scaling your Neural Networks to adapt to different vehicles and scenarios
What We're Looking For
- Masters or PhD in Computer Vision, Artificial Intelligence, Electrical Engineering, Physics, Mathematics or some other related field
- 5+ years of professional experience working with real-world, physical data or live-stream data, including live sensor data, market models and physics engines
- Extensive experience developing and optimising Deep Neural Network Algorithms
- Familiarity with various computer vision areas such as SLAM, Teacher Tasks, LSTM, YOLO, Multi-Object Tracking and Semantic Segmentation
- Strong programming skills in Python or C++, functional programming is beneficial
- Fluency the core principals of mathematics and physics concepts to solve complex problems, 3D Modelling is a plus
- A track record of having brought models end-to-end through from conception to post-production
- Standout communication skills, and can work cross-functionally with a high skill team
- For Managers and Tech Leads: The ability to lead long-term strategy and work with leadership to build out teams and assign tasks, including hiring, firing and organizing teams
The compensation for this role consists of a base salary and pre-IPO equity, which the base salary is expected to range from $175,000 - $300,000. Various factors including the candidate's overarching experience will influence the base pay offered within the range. This salary range is reflective of a position based in San Francisco, CA. If authorization is granted to work outside of that area, geographic adjustment (according to a specific city and state) will be made.
Ourselves and Our Client
We are committed to equal employment opportunity. We will not discriminate against employees or applicants for employment on any legally‑recognized basis ["protected class"] including, but not limited to: veteran status, uniform service member status, race, color, religion, sex, national origin, age, physical or mental disability or any other protected class under federal, state or local law.