Artificial Intelligence Engineer

Remote, USA Full-time
HomeTeam Network is seeking an AI Engineer to develop solutions for their AI-complete sports broadcasting platform. The role involves working on computer vision and machine learning systems to enhance sports video processing and real-time content generation. Responsibilities Implement and optimize computer vision models for real-time player tracking, action recognition, and game state detection in sports video Build ML inference pipelines using ONNX Runtime and TensorRT for GPU-accelerated model deployment Develop multiprocess video processing pipelines for high-throughput RTMP/RTSP/SRT streams Integrate AI systems with AWS infrastructure (ECS, Lambda, Step Functions, EventBridge) and cloud deployment workflows Optimize real-time video processing performance using FFmpeg, OpenCV, and CUDA Deploy and monitor AI models in cloud‑native production using cloud platforms and Weights & Biases for end‑to‑end observability Create testing frameworks to validate model accuracy and pipeline reliability Collaborate with DevOps on infrastructure-as-code using Terraform for AWS and GCP deployments Research and implement emerging AI technologies to improve our platform Skills 1-3 years of software development experience (AI/ML focus preferred) Strong Python programming skills with experience in: Deep learning inference frameworks (ONNX Runtime, TensorRT) Computer vision libraries (OpenCV, torchvision) Data processing and numerical computing (NumPy, Pandas) Multiprocessing and concurrent programming Understanding of ML fundamentals and neural network architectures Experience with Git and collaborative development practices Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience) Ability to troubleshoot complex technical issues in production systems Excellent communication and teamwork skills Experience with video streaming protocols (RTMP, RTSP, SRT) and FFmpeg Knowledge of real-time system optimization and low-latency processing Experience with cloud infrastructure (AWS ECS, Lambda, Step Functions, or GCP equivalents) Understanding of MLOps practices and model deployment pipelines Familiarity with infrastructure-as-code tools (Terraform) Experience with experiment tracking tools (Weights & Biases, MLflow) Published research in computer vision or machine learning Company Overview We know how hard it can be for families to travel across cities, provinces, and even countries to watch their children and loved ones participate in sports. It was founded in 2021, and is headquartered in Regina, Saskatchewan, CAN, with a workforce of 2-10 employees. Its website is
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