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 current 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.

Required Skills

- Computer vision / Perception
- Machine Learning

📌 Lead Engineer I - CVML (Bengaluru)
🏢 NewSpace Research & Technologies
📍 Bengaluru