Computer Vision Engineer

COMPUTER VISION ENGINEER
Job Description

Qualifications:
Mtech/MS/Bachelor in CS, ECE or related fields with 3+ years of relevant experience
Experience in optimizing software systems for CPU / GPUs.
Experience with compiler framework design(llvm/MLIR), Vector processing and graph based optimizations
Strong statistics, applied math skills for real world HPC and Deep learning problems
Experience in any Machine learning/ Deep Learning Benchmarking process/tools
Strong coding skills in C++,Python and low level intrinsics
Good communication skills
Ability to work in a dynamic, cross-geo, startup-like environment

Roles and Responsibilities
Computer vision/Video intelligence
Python 3.8+
OpenCV
Deep Learning models building
Objects detection: Yolo v5 like models building
Multi-person pose estimation
Objects tracking
Speed estimation
Camera object position estimation
2D/3D mapping of objects and moving objects
Multi-camera fusion
Edge computation camera-specific development
camera types (standard, Infrared, FRID)
camera build extra sensors integration
code and model optimization to work in reduced resources in real-time (GPU, TPU)
edge development/deployment
integration with camera sensors, building algorithms embedded in the camera
General development
Git
Docker
Static code analysis, code optimization
Industry/academic experience with machine learning and computer vision programming using libraries such as PyTorch, TensorFlow, OpenCV, Caffe
Strong project experience involving algorithm development for computer vision applications.
Demonstrated past algorithm development in at least one area within machine learning like neural networks, clustering, object tracking.
Experience with object classification, gesture recognition or human pose estimation and training deep neural networks using synthetic and artificial data.
Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods and linear algebra.
Self-motivated individual with passion towards state-of-the-art computer vision technologies.