ML Engineer

Requirements:

• Experience and coding Background: 4-6 years building and shipping machine-learning systems in production, with a solid record of taking models from research to deployment.
• Strong Coder (must-have): Excellent, demonstrable coding ability; clean, efficient, production code; solid data structures, algorithms, and complexity fundamentals. A public code profile (GitHub / competitive programming) is a strong plus. Machine Learning
• Core ML/DL: Deep, hands-on experience with PyTorch (and/or TensorFlow); CNNs, sequence/temporal models, and the training/evaluation lifecycle end to end.
• Applied Depth: Strength in one or more of computer vision/pose estimation, multimodal or vision-language models, or real-time/time-series modeling. Computer Vision (mid-level required) Working CV: Solid, hands-on proficiency with OpenCV and image/video processing.
• Applied Geometry / Pose: Practical experience with camera calibration, multi-view geometry, or 2D/3D pose estimation. Deep specialization is not required, but real, hands-on CV exposure is, since it feeds the models you build.