AI/ML Engineer for Pet Health Image and Video Classification (Stool, Coat, Diet, Gait, and More)

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PicVet is building the world’s most comprehensive AI-powered mobile app for pet wellness. Our goal is to use image and video analysis to identify early signs of health issues in pets—from coat dullness and gum redness to abnormal posture and stool consistency. We’re seeking an experienced AI/ML engineer (or small team) to help us design, train, and deploy lightweight image and video models across 8 diagnostic categories: Categories Include: Stool analysis (normal, soft, bloody, mucus) Coat condition (shiny, dull, shedding, parasites) Eye health (clear, red, discharge, cloudy) Diet recognition (wet food, kibble, raw meat, human food) Skin and wound detection (rashes, lesions, scabs) Teeth and gum condition (tartar, redness, missing teeth) Ear condition (wax buildup, redness, discharge) Posture and gait analysis (limping, stiffness – from short video clips) Scope of Work: Advise on and source training datasets (we’ll support clinical/vet data where needed) Train classification and detection models (EfficientNet, YOLOv8, OpenPose, or best-fit) Optimize models for low-latency inference (TorchScript, TensorFlow Lite, or ONNX) Deploy APIs using FastAPI or TorchServe (mobile-ready endpoints) Collaborate with our mobile developer for integration and testing Help set performance benchmarks (latency, accuracy, size per model) Requirements: Demonstrated experience training and deploying image classification or object detection models Strong with PyTorch or TensorFlow, and cloud inference tools (e.g. GCP, AWS, TorchServe, etc.) Experience working with real-world or medical imaging data preferred Bonus: familiarity with pose estimation, synthetic data augmentation, or veterinary datasets Excellent documentation and async communication skills

Keyword: Data Analysis

Price: $65.0

PyTorch TensorFlow Image Classification Object Detection Medical Imaging Artificial Intelligence Machine Learning