Machine Learning Engineer, NVH develops advanced machine learning systems that help Tesla improve product diagnostics and quality across its vehicles and technologies. Based in Richmond Hill, this role combines artificial intelligence, audio processing and engineering to create tools that support manufacturing and customer satisfaction. The role is about building diagnostic models, managing those data pipelines and getting machine learning solutions out of the lab and into real production environments. You will work across teams in manufacturing, quality and vehicle engineering and the work feeds straight into how Tesla spots product issues and tackles them at scale. Tesla gives you the chance to engage with tough technology that really affects its products and customers world wide. Check the job details below to get more context. Company Name :

Tesla Location :

Richmond Hill, Ontario, Canada Salary :

$76,000 – $138,000/annually Job Type :

Full time Start date :

As soon as possible Benefits :

Health coverage, dental care, vision coverage, life insurance, disability protection, RRSP matching contributions, employee stock purchase plan, employee assistance resources, parental support programs, paid sick leave, vacation time, paid holidays, Tesla family benefits, product savings, wellness discounts and additional employee rewards. Job Description

Machine Learning Engineer, NVH is a machine learning and software engineering role within Tesla’s Noise, Vibration and Harshness team. This is a full time position based in Richmond Hill, Ontario. The role focuses on developing diagnostic systems for Tesla vehicles and products. The position combines machine learning, audio processing and production deployment work.



The work setting is research driven, technology focused and team oriented. Employees receive competitive compensation, stock awards, benefits and access to innovative engineering projects. Responsibilities

Design, develop and deploy machine learning models and audio algorithms for NVH diagnostics. Build and maintain machine learning pipelines from data collection through production deployment. Work with manufacturing, quality audit and vehicle engineering teams to integrate diagnostic systems. Improve model performance through testing, experimentation and iterative development. Develop tools and frameworks for collecting data, labelling and model monitoring. Work to develop coding standards, testing practices, documentation and reproducibility. Review developments in audio machine learning, signal processing and deep learning. Apply relevant research advancements to Tesla’s diagnostic challenges. Requirements

A degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science or a related field is required, or equivalent work background. Strong knowledge of Python and C++ is required. Solid background in software engineering practices including version control, testing and code review is required. Strong knowledge of machine learning fundamentals including neural networks, optimization methods, regularization and model evaluation is required. Work background with neural network architectures for audio applications including CNNs, RNNs and Transformers is required. Strong knowledge of event detection and of classification models. Skilled in PyTorch or another major deep learning tool such as TensorFlow. Can work with machine learning systems from development through deployment in production environments.

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📌 Machine Learning Engineer (Winnipeg)
🏢 Tobermory
📍 Winnipeg