Deep Learning Engineer
Core
Design and deploy computer vision and deep learning models to help athletes maximize performance.
Role type
Deep Learning Engineer (Computer Vision)
Builds
Computer vision and machine learning products for sports analytics
Domain
Sports technology / Computer Vision
Deliverable
production ML models
Required skills
Python, PyTorch or TensorFlow, computer vision fundamentals, Blender, Linux, Git, Docker
Preferred skills
MLflow, Weights & Biases, DVC, ClearML, Kubeflow, TensorRT, ONNX Runtime, TensorFlow Lite, C++, multi-object tracking, pose estimation
Technologies
PyTorch, TensorFlow, Blender, Linux, Git, Docker, MLflow, Weights & Biases, DVC, ClearML, Kubeflow, TensorRT, ONNX Runtime, TensorFlow Lite
Responsibilities
Own the full deep learning model lifecycle from data collection to deployment; Design and improve data collection, labeling, and annotation pipelines; Train, evaluate, and optimize detection, segmentation, keypoint, and tracking models; Develop synthetic datasets using Blender and Python-based rendering pipelines; Build and maintain reproducible MLOps pipelines including experiment tracking and dataset versioning; Optimize models for deployment on embedded hardware; Define evaluation benchmarks and ensure model quality through automated testing
Seniority
Mid-level, hands-on IC
