Technical Lead Engineer - Computer Vision

The Role

We're looking for a Technical Lead who can own and drive our Computer Vision initiatives end-to-end. This is a hands-on leadership role, you'll be writing code, reviewing architectures, mentoring developers, and serving as the primary technical point of contact for our customers.

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What You'll Do

• Lead a team of Computer Vision developers, providing technical direction and mentorship

• Architect, develop, and optimize CV algorithms and pipelines

• Coordinate directly with customers to understand requirements, provide updates, and ensure delivery excellence

• Oversee deployment of CV solutions on NVIDIA GPU infrastructure (A4500, L4, and similar) and Jetson edge devices (Orin, Xavier, and similar), Raspberry Pi, and similar devices.

• Conduct code reviews and establish best practices for the team

• Balance individual contribution with team leadership, we expect you to stay close to the code

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What We're Looking For

• 5+ years of experience in Computer Vision, with at least 2 years in a lead or senior role

1. Strong DSA (Data Structures & Algorithms) Must be able to code and implement, not just theory
2. YOLO model experience
3. Practical experience working on YOLO-based computer vision models
4. Good communication skills
5. • Strong proficiency in C++ is required; hands-on experience with DeepStream, GStreamer, and Video Analytics is mandatory.

• Strong proficiency in Python and deep learning frameworks (PyTorch, TensorRT, CUDA)

• Hands-on experience with video analytics, object detection, tracking, segmentation, or recognition systems.

• Experience in deploying computer vision pipelines in production.

• Experience with NVIDIA Jetson platform (Orin, Xavier, or similar)

• Familiarity with NVIDIA GPU deployment workflows (CUDA, TensorRT, DeepStream is a plus)

• Experience managing or mentoring a team of 3+ developers

• Strong communication skills, you'll be the face of our technical team to customers

• Ability to context-switch between writing code and leading people

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Nice to Have

• Optimizing GStreamer, and DeepStream applications with CUDA and TensorRT.

• Experience with model optimization, compression, and model quantization.

• Background in ANPR, video analytics, or industrial vision systems

• Exposure to Vision Language Models or generative AI and frameworks like vLLM, SGLang.