AI Platform Engineer
Core
Build and operate scalable AI data, training, evaluation, and MLOps infrastructure to support efficient development, validation, and management of AI models for perception, prediction, VLA, and scheduling optimization teams.
Role type
Senior IC AI Platform Engineer (MLOps & Data Infrastructure)
Builds
Data pipelines, dataset management systems, training/evaluation platforms, and model lifecycle infrastructure for autonomous vehicles and mining equipment.
Domain
Industrial AI / Autonomous Systems / MLOps
Deliverable
production ML models
Required skills
Python, distributed training, Kubernetes, Docker, MLflow, Ray, Airflow, CI/CD, model registry, data lineage, experiment tracking
Preferred skills
VLM/VLA data management, reinforcement learning platforms, large-scale sensor data processing, LLM/LLMOps, industrial AI scenarios
Technologies
PyTorch, TensorFlow, Kubeflow, SageMaker, Kubernetes, Docker, MLflow, Ray, Airflow
Responsibilities
Build data collection and storage capabilities for vehicle and site data; establish dataset versioning and annotation workflows; construct reusable training tasks and compute scheduling; maintain model registry and lifecycle processes; provide model deployment pipelines and rollback mechanisms; ensure platform reliability and developer experience.
Seniority
Senior, hands-on IC
