Computer Vision/Embedded Engineer (C++, DeepStream)

Brief DescriptionTrois Infotech is seeking a Computer Vision/Embedded Engineer to join our team in Trivandrum. This full-time, on-site position involves developing and implementing advanced computer vision algorithms, as well as conducting research and development in areas like pattern recognition, robotics, and computer vision. The successful candidate will work closely with cross-functional teams to seamlessly integrate computer vision solutions into our products. The Research and development and Productization include Face Recognition, WiFi (IEEE 802.11ah),4G LTE and 5G, ensuring reliable data transmission, Real-Time and Edge based Computer Vision Processing etc. Experience: 2-4 years (Experience requirements may be relaxed for highly proficient candidates as determined during the interview process.) Key Responsibilities: · High-accuracy edge processing for facial recognition (FR) and incident detections. · Develop and maintain reusable, testable, and efficient production code for machine learning and deep learning pipelines in computer vision. · Design and implement low-latency, high-availability, and high-performance applications. · Assess, prioritize, and implement feature requests based on technical requirements. · Collaborate with internal teams to understand user needs and deliver technical solutions. · Integrate front-end elements developed by UI/UX teams with server-side logic. · Implement and manage data storage solutions, including databases, key-value stores, and blob storage.Preferred SkillsRequired Skills and Qualifications: · Programming Languages: Proficiency in Python combined with one of the following: C++, Rust, Java, or Kotlin. Experience developing computer vision models with frameworks such as Jax, TensorFlow 2, or PyTorch is essential. Candidates proficient in Python combined with C++ or Rust will be prioritized. · Deployment Experience: Experience deploying models and computer vision pipelines using ONNX Runtime, TensorRT, and DeepStream Runtime. · CUDA-C/OpenCL-C: Strong familiarity with these technologies is highly advantageous. · Computer Vision and Image Processing: Demonstrated problem-solving skills in image processing and computer vision, with a deep understanding of modern machine learning methods and deep learning architectures (e.g., object detection, segmentation, image classification using Deep Neural Networks). The ability to conceptualize zero-shot architectures for various computer vision tasks is important. Candidates may be required to code specific DNN architectures and perform image processing routines during the interview. · Linux Proficiency: Strong command-line skills are required, as much of the work will be performed on remotely connected edge AI/IoT devices. · Scalable Application Design: Solid understanding of the principles behind designing scalable applications. · API Development: Ability to write and consume HTTP REST and Streaming APIs using Python, Java, or Rust. · Platform Optimization: Understanding the differences between multiple delivery platforms (e.g., mobile vs. desktop) and optimizing output for specific platforms.