Machine Learning Engineer, NVH
Core
Design, develop, and deploy machine learning models and audio algorithms for advanced Noise, Vibration, and Harshness (NVH) diagnostics across Tesla's vehicle and product lineup to impact product quality and customer experience.
Role type
Machine Learning Engineer (Audio/Signal Processing)
Builds
Production ML pipelines for NVH diagnostics integrated into manufacturing lines
Domain
Automotive manufacturing / Audio signal processing
Deliverable
production ML models
Required skills
Python, C++, neural network architectures (CNNs, RNNs, Transformers), PyTorch, deep learning fundamentals, software engineering best practices
Preferred skills
experience with event detection and classification models, knowledge of signal processing
Technologies
PyTorch, TensorFlow, C++, Python
Responsibilities
Design and deploy ML models for NVH diagnostics; build end-to-end ML pipelines from data ingestion to production; collaborate with manufacturing and engineering teams to integrate algorithms; drive model performance improvement through experimentation; develop tooling for data collection, labeling, and monitoring; define best practices in ML engineering
Seniority
Mid-to-Senior, hands-on IC