Lead Engineer I - Systems

Key Responsibilities Multidisciplinary Team Leadership o Lead an engineering team to build out , scaling the perception organization pipeline comprising Robotics, CV/ML, Data, Software, Embedded, and Integration engineering disciplines by aligning technical efforts, resolving cross-functional challenges, and driving mission-focused execution o Own hiring, mentoring, and infrastructure investments critical to team success. o Maintain hands-on technical oversight while optimizing performance, driving innovation, and ensuring stakeholder clarity. Full-Stack Perception System Ownership o Manage the perception technology roadmap, systems architecture, and product execution, leveraging robotics, CV/ML, and high-quality software engineering to bring state-of-the-art solutions to market o Prototype system concepts, validate hypotheses, and contribute to product roadmaps o Conduct system analysis to identify bottlenecks and propose architectural or algorithmic improvements o Evaluate and integrate new technologies, frameworks, and accelerators based on program requirements Leading the Perception Software Development Team comprising of the following responsibilities: o Engineer high-quality software systems and integration architecture the core of this team including: Architecting end-to-end perception systems spanning edge platforms and GCS infrastructure to provide operators with comprehensive situational awareness. Integration of third-party software and sensor systems with the perception stack. Validation of system integration with the autonomy stack across simulated and operational environments o Develop sensor data acquisition and preprocessing methodologies encompassing sensor data handling, interpretation, and synchronization; sensor control including configuration, rates, and gimbal behavior; and image processing techniques o Develop, optimize, deploy, and maintain perception models including CV/ML architectures such as object detection, segmentation, tracking, and Vision Language Models; complementary image processing techniques including image matching and Structure from Motion; deployment on edge devices (such as NVIDIA SOCs) with performance optimization; secure development practices across the ML deployment lifecycle; and data curation and maintenance workflows MLOps. o Apply robotics engineering methodologies to define perception-driven robot behaviors such as desired platform trajectories, sensor parameters, and multi-robot target search strategies. Required Qualifications Bachelor s or Master s degree in Computer Science, Electrical Engineering, or related field. Proven expertise in C++/Python and designing reliable software systems. Technical Leadership : Demonstrated leadership in guiding a multidisciplinary team, with hands-on contributions in core areas and clear technical direction in others. Perception Systems and Software Engineering : o Proven ability to own and evolve an end-to-end perception pipeline (from sensors through inference to output translation), collaborating with specialists for advanced model development, MLOps, or embedded optimization as needed. o Comfortable working across edge devices and backend systems. o Proficiency integrating third-party libraries, sensor SDKs, and external frameworks. o Ability to identify bottlenecks, propose architectural improvements, and validate solutions through simulation and testing. ML/CV and Systems Knowledge: o Working knowledge of modern architectures, training pipelines, and model optimization o Understanding of MLOps concepts, data curation, and model lifecycle management Domain Depth: o Deep expertise in at least one of: edge deployment (NVIDIA SOCs), MLOps/ML pipelines, or robotics/UAV/autonomous vehicles perception systems o Ability to learn and operate competently in adjacent domains Desired Skills Familiarity with UAV systems or real-time autonomy stacks. Familiarity with ROS or robotics frameworks. Background in secure coding or Secure SDLC processes. Experience in algorithms for multi-robot coordination and behaviors. Vision Language Models, or advanced geometric computer vision algorithms. Experience with Active Learning, Domain Adaptation, or edge-platform porting. Required Skills Computer vision / Perception Machine Learning