Drive deep technical work across perception, localization and mapping, planning, and control.
Define and enforce stable API contracts between autonomy components and raise production software quality.
Partner with research collaborators to translate cutting-edge research into robust, deployed capabilities.
FieldAI builds risk-aware, field-ready AI systems for legged and wheeled robots, combining rigorous engineering with learning systems. The company has a world-class team with experience from DeepMind, NASA JPL, Boston Dynamics, and other leading organizations, focused on reliable deployment outside the lab.
Design and maintain robotics middleware using modern C++ on embedded Linux.
Own platform components from architecture to deployment and fleet operations.
Collaborate with autonomy, systems, and hardware teams on safety and reliability.
The company builds and evolves embedded software platforms for a fleet of autonomous delivery robots. It fosters a collaborative, cross-functional engineering culture focused on reliability, safety, and professional growth.
Develop and evaluate deep learning models for feature detection, matching, depth estimation, and visual localization.
Own data preparation, training workflows, and evaluation of learned components for vision-based navigation.
Partner with state estimation and deployment engineers to integrate and optimize models for onboard systems.
Shield AI is a venture-backed defense-tech company developing intelligent systems to protect service members and civilians, with products like Hivemind autonomy software and V-BAT aircraft. It has offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, actively supporting operations worldwide.
Develop deep learning models for feature matching, depth estimation, pose estimation, and image-to-map localization.
Own data preparation and supervision strategies, including dataset curation, labeling workflows, and quality checks.
Collaborate with state estimation and deployment engineers to integrate learned measurements into VIO and terrain-relative navigation systems.
This company builds autonomous systems that can understand motion and localize themselves when GPS is unavailable. Its engineering team works remotely, collaborating across deep learning, computer vision, and state estimation.
Design, develop, and deploy production ML models for ego-motion estimation and localization using camera, LiDAR, and radar.
Develop scalable training and evaluation workflows with PyTorch and large-scale real-world datasets.
Collaborate with cross-functional teams and provide technical leadership in design reviews and mentoring.
Torc develops autonomous vehicle software for automated trucks, aiming to transform freight movement. As part of the Daimler family, they have a collaborative, energetic, and team-focused culture with competitive benefits.