Summary
Overland AI, founded in 2022 and based in Seattle, Washington, is focused on transforming land operations for modern defense through advanced robotics and machine learning. They are seeking perception experts to design and deploy deep learning algorithms for autonomous vehicles, collaborating across disciplines to enhance system performance and reliability.
Responsibilities
- Design, prototype, and deploy perception/deep learning algorithms (e.g., object detection and tracking, surface reconstruction, visual odometry) that run real-time on our autonomous vehicles
- Identify, implement, and respond to meaningful metrics that affect vehicle behavior
- Support experimentation and integration of the perception stack with new sensors and configurations (C++)
- Collaborate closely with experts across disciplines to work across the entire stack to improve the reliability and performance of the system
Skills
- BS/MS/PhD in Computer Science or similar
- 2+ years of experience (industry or academia) implementing perception algorithms
- Expert in ROS 2 or other similar robotics middleware
- Strong programming (C++ or Python) skills and experience in a deep learning framework such as Pytorch, JAX, Tensorflow, etc
- Ability to obtain and maintain a DOD Security Clearance
- Top-tier publications in CV and Robotics conferences and/or past experience working with lidars and cameras
Qualifications
Must Haves
- BS/MS/PhD in Computer Science or similar
- 2+ years of experience (industry or academia) implementing perception algorithms
- Expert in ROS 2 or other similar robotics middleware
- Strong programming (C++ or Python) skills and experience in a deep learning framework such as Pytorch, JAX, Tensorflow, etc
- Ability to obtain and maintain a DOD Security Clearance
Nice to Haves
- top-tier publications in CV and Robotics conferences and/or past experience working with lidars and cameras
Benefits
- Equity compensation
- Best-in-class healthcare, dental and vision plans.
- Unlimited PTO
- 401k with company match
- Parental leave