AI Platform & Machine Learning Engineer
Core
Build scalable infrastructure for training, deploying, and monitoring machine learning models for wearable AI systems in construction.
Role type
Senior Machine Learning Engineer (AI Platform)
Builds
Production-ready AI infrastructure, dataset management pipelines, model training/retraining systems, and deployment pipelines for cloud and embedded devices.
Domain
Construction technology, Computer Vision, Embedded AI
Deliverable
production ML models
Required skills
Python, PyTorch, end-to-end ML lifecycle management, distributed training, CI/CD, Docker, Kubernetes, cloud deployment, software engineering fundamentals
Preferred skills
MLflow, Weights & Biases, Ray, Kubeflow, Airflow, LoRA, PEFT, NVIDIA Jetson, CUDA, TensorRT, ONNX, AWS/Azure/GCP, large-scale dataset management
Technologies
PyTorch, Docker, Kubernetes, MLflow, Weights & Biases, Ray, Kubeflow, Airflow, NVIDIA Jetson, CUDA, TensorRT, ONNX, AWS, Azure, GCP
Responsibilities
Design scalable infrastructure for training and deploying ML models; develop distributed training pipelines and reproducible environments; build experiment tracking and model versioning systems; create automated benchmarking and validation pipelines; manage large-scale dataset ingestion and annotation workflows; optimize inference infrastructure and build scalable APIs; support federated learning and continual learning pipelines; deploy models to cloud and embedded NVIDIA platforms.
Seniority
Senior, hands-on IC