·       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.

·       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

 

·       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.