Software / System Engineer

Responsibilities:

• Core Pipeline Engineering: Design and build efficient data pipelines in C/C++ and Python for handling low-latency video feeds and data flows.
• Systems and Service Integration: Connect performant C/C++ modules with backend services, APIs, and modern application frameworks.
• Full-Stack and Product Development: Participate across the tech stack, from backend logic and performance profiling to connecting frontend dashboards and user interfaces.
• Model Training and Deployment: Work on training, fine-tuning, and deploying deep learning models to production.
• Optimize for the Edge: Work on deploying models to edge devices (NVIDIA Jetson) using runtime engines like TensorRT and ONNX Runtime.

Requirements:

• Solid Engineering Foundations: Strong command over data structures, algorithms, memory management, and operating system internals (threading, IPC, and dynamic memory allocation).
• Coding Proficiency: Fluency in C/C++ and Python. You know how to write clean, maintainable, and memory-conscious code.
• Problem-Solving Aptitude: Strong analytical ability, structured debugging mindset, and quick learning agility (demonstrated through solid academic projects, competitive programming, or open-source contributions).
• Degree Background: B. Tech / B. E. / M. Tech in Computer Science, Mathematics, Electrical Engineering, or a related quantitative field.

Nice to have:

• Hands-on experience in these areas is not strictly required, but curiosity and foundational knowledge are a huge plus
• Machine Learning Fundamentals: Exposure to PyTorch, model inference runtimes, or deep learning concepts.
• Computer Vision Basics: Basic exposure to OpenCV, object detection architectures (e. g., YOLO variants), or tracking algorithms.
• Hardware and Acceleration: Curiosity about GPU acceleration (CUDA, TensorRT) or embedded hardware (NVIDIA Jetson).
• Modern Web/API Development: Familiarity with building backend APIs or modern web development.