Key Responsibilities
Multidisciplinary Team Leadership
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
Own hiring, mentoring, and infrastructure investments critical to team success.
Maintain hands-on technical oversight while optimizing performance, driving innovation, and ensuring stakeholder clarity.
Full-Stack Perception System Ownership
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
Prototype system concepts, validate hypotheses, and contribute to product roadmaps
Conduct system analysis to identify bottlenecks and propose architectural or algorithmic improvements
Evaluate and integrate new technologies, frameworks, and accelerators based on program requirements
Leading the Perception Software Development Team comprising of the following responsibilities:
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
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
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.
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:
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.
Comfortable working across edge devices and backend systems.
Proficiency integrating third-party libraries, sensor SDKs, and external frameworks.
Ability to identify bottlenecks, propose architectural improvements, and validate solutions through simulation and testing.
ML/CV and Systems Knowledge:
Working knowledge of modern architectures, training pipelines, and model optimization
Understanding of MLOps concepts, data curation, and model lifecycle management
Domain Depth:
Deep expertise in at least one of: edge deployment (NVIDIA SOCs), MLOps/ML pipelines, or robotics/UAV/autonomous vehicles perception systems
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.