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How much do seasonal model validation jobs pay per hour?

As of May 29, 2026, the average hourly pay for seasonal model validation in the United States is $52.00, according to ZipRecruiter salary data. Most workers in this role earn between $39.42 and $63.22 per hour, depending on experience, location, and employer.
What are the most commonly searched types of Model Validation jobs? The most popular types of Model Validation jobs are:
Seasonal Model Validation jobs near you
Machine Learning Engineer, Global Supply Chain

Machine Learning Engineer, Global Supply Chain

Tesla

Fremont, CA • On-site

Full-time

Posted 17 days ago

Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers

Job description

Job Summary:
Tesla is seeking a highly skilled Machine Learning Engineer to join the Supply Chain Engineering team. The role involves designing, developing, and deploying machine learning models for supply chain forecasting and optimization.
Responsibilities:
• Design, develop, and implement machine learning models for supply chain forecasting, including demand prediction, inventory optimization and risk assessment using techniques like supervised learning, convolutional neural networks, and tools such as PyTorch and Pandas
• Collaborate with supply chain planners to integrate ML models into existing platforms, ensuring real-time decision making for supplier selection, warehouse allocation, reduce costs and mitigate part availability risks
• Perform model validation and performance monitoring to ensure models maintain high accuracy
• Take ownership of production models, ensuring robust alerting systems for rapid issue resolution
• Work with diverse, heterogeneous datasets (supply, demand, seasonal variation) to build scalable solutions
• Translate ambiguous problem statements into actionable, end-to-end machine learning models
• Follow agile development practices and maintain high standards for clean, modular, and sustainable code
Qualifications:
Required:
• Proven experience in scaling and optimizing inference for large ML models, particularly transformers or similar architectures
• Familiarity with quantization-aware training, model compression, and distillation for edge and real-time inference
• Proficiency with Python and C++ and deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Strong understanding of computer systems and architecture, with experience deploying ML models on GPUs, TPUs, or NPUs
• Hands-on expertise with CUDA programming, low-level performance profiling, and compiler-level optimization (TensorRT, TVM, XLA)
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

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