Sensor Integration Engineer
16 hours ago
Company background
Swarmbotics AI is a low-cost, swarm robotics company for industry and defense. We see a world of ubiquitous low-cost robots transforming almost all aspects of society, but we see an urgent need in the defense industry. We focus on building swarms of robots that incorporate a low-cost BOM, an autonomous stack optimized for off the shelf components, and a global planner that enables swarm capabilities for groups of robots to accomplish sophisticated tasks.
Our first product is a defense application building Unmanned Ground Vehicles (UGVs), collectively termed - Attritable, Networked, Tactical Swarm (ANTS). Each UGV in ANTS is an independently-tasked, attritable robot designed for on-demand and autonomous mobility. When operating as a swarm, ANTS is capable of executing more advanced and coordinated, high-level capabilities across a battlespace. ANTS will help solve some of the DoD’s biggest problems that will save lives and increase defense capabilities.
Stephen Houghton and Drew Watson are the Founders and have decades of experience in self-driving cars and trucks, humanoids, and UAVs with experience from NASA, JPL, Cruise, Embark, McKinsey, Amazon, and the CIA.
Position Description
Swarmbotics is seeking a skilled Sensor Integration Engineer to advance our autonomous ground vehicle platforms for defense applications. This engineer will be responsible for the design, integration, and calibration of diverse sensor suites that enable precise perception, navigation, and environment mapping in off-road and unstructured terrains. Working closely with the perception and controls engineers, you will ensure optimal sensor performance and data fidelity in dynamic and rugged environments, directly contributing to Swarmbotics' product roadmap.
Required Qualifications
- Ability to thrive in a fast-paced, evolving startup environment
- Strong expertise in integrating sensors such as LIDAR, cameras, GPS, IMUs, and wheel encoders
- First hand experience developing sensor calibration processes in a production environment
- Familiarity with sensor fusion and real time data processing in hardware and software robotics stack
- Proficiency in C++ and/or Python
- Demonstrated ability to optimize sensor data for autonomous vehicle navigation
- BS in Robotics, Electrical Engineering, Computer Science, Computer Engineering, or a related field
- Commitment to advancing national defense initiatives and supporting allied operations
- Ability to obtain and maintain a U.S. security clearance
Preferred Qualifications
- MS or PhD in Robotics, Electrical Engineering, or a related field
- Experience developing sensor systems for autonomous off-road navigation
- Experience integrating additional sensor types, to include 2-way audio, radar, etc.
- Experience with hardware-in-the-loop testing and real-world validation
- Experience working with robotic middleware like ROS2
- Knowledge of system architecture and integration best practices
- Willingness to relocate to the Phoenix, AZ area
The preceding description is not designed to be a complete list of all duties and responsibilities required for the position. Swarmbotics is an equal-opportunity employer. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, caste, creed, religion, sex, gender identity, sexual orientation, national origin, ancestry, disability, uniform service, Veteran status, age, or any other protected characteristic per federal, state, or local law.
The preceding description is not designed to be a complete list of all duties and responsibilities required for the position. Swarmbotics is an equal-opportunity employer. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, caste, creed, religion, sex, gender identity, sexual orientation, national origin, ancestry, disability, uniform service, Veteran status, age, or any other protected characteristic per federal, state, or local law.
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