Senior Research Engineer – Localization & Planning

The Mission Robust localization and motion planning in GPS-denied and contested environments is one of our core research challenges. We are looking for a Senior Research Engineer who will not just integrate existing solutions, but actively advance the state of the art for our specific operational context. Working as a highly autonomous individual contributor, you will bridge the gap between theoretical research and field-deployable code.

Expected Outcomes

Research Ownership:

Co-own the localization and planning research roadmap in direct collaboration with autonomy lead.

Rapid Delivery:

Deliver one proof-of-concept improvement to localization in GPS-denied conditions within your first 3 months.

Establish Standards:

Develop rigorous benchmarking methodologies to evaluate algorithmic performance in simulation and on hardware platforms.

Сore responsibilities

Algorithm Development:

Design, implement, and optimize algorithms for SLAM, state estimation, and motion planning to enable intelligent autonomous behavior.

System-Level Integration:

Develop robust, modular software systems interfacing with hardware components (sensors, embedded controllers) within ROS2 architectures.

Knowledge Contribution:

Summarize findings from academic papers, conduct original investigations, and apply rigorous mathematical modeling to support algorithmic design.

Cross-Functional Collaboration:

Work closely with hardware, embedded, and software teams to ensure seamless integration, while providing technical mentorship to junior engineers.

Qualifications & Competencies

Education:

MS or PhD in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field.

Experience:

5+ years in robotics-focused R&D with a strong track record of solving technical challenges end-to-end. Proven publications or an equivalent applied research track record.

Technical Stack:

Proficiency in C++ and/or Python within the ROS2 ecosystem.

Mathematical Rigor:

Deep theoretical understanding of Bayesian filtering, optimization, and differential geometry.

Domain Expertise:

Hands-on experience with SLAM, control systems, and motion planning.