... seasonal variation) to build scalable solutions • Translate ambiguous problem statements into ... on expertise with CUDA programming, low-level performance profiling, and compiler-level ...
... seasonal variation) to build scalable solutions • Translate ambiguous problem statements into ... on expertise with CUDA programming, low-level performance profiling, and compiler-level ...
... seasonal variation) to build scalable solutions • Translate ambiguous problem statements into ... on expertise with CUDA programming, low-level performance profiling, and compiler-level ...
... seasonal variation) to build scalable solutions • Translate ambiguous problem statements into ... on expertise with CUDA programming, low-level performance profiling, and compiler-level ...
... as seasonal or temporary employment. The benefits that generally apply to regular, full-time ... GPU programming experience (CUDA/OpenCL). - Publications in robotics and computer vision ...
... as seasonal or temporary employment. The benefits that generally apply to regular, full-time ... GPU programming experience (CUDA/OpenCL). - Publications in robotics and computer vision ...
... as seasonal or temporary employment. The benefits that generally apply to regular, full-time ... CUDA, NVIDIA Warp, or similar). - Contributions to open-source robotics or simulation projects.
... as seasonal or temporary employment. The benefits that generally apply to regular, full-time ... CUDA, NVIDIA Warp, or similar). - Contributions to open-source robotics or simulation projects.
Seasonal Cuda Developer information
See salary details
$17.07 - $22.95
8% of jobs
$22.95 - $28.82
3% of jobs
$28.82 - $34.70
6% of jobs
$40.37 is the 25th percentile. Wages below this are outliers.
$34.70 - $40.58
7% of jobs
$40.58 - $46.46
14% of jobs
$46.46 - $52.34
9% of jobs
The median wage is $52.97 / hr.
$52.34 - $58.22
15% of jobs
$62.94 is the 75th percentile. Wages above this are outliers.
$58.22 - $64.10
15% of jobs
$64.10 - $69.97
12% of jobs
$69.97 - $75.85
7% of jobs
$75.85 - $81.73
3% of jobs
$17
$52
$81
How much do seasonal cuda developer jobs pay per hour?
As of Jul 6, 2026, the average hourly pay for seasonal cuda developer in the United States is $52.84, according to ZipRecruiter salary data. Most workers in this role earn between $40.38 and $64.66 per hour, depending on experience, location, and employer.
What cities are hiring for Seasonal Cuda Developer jobs? Cities with the most Seasonal Cuda Developer job openings:
What are the most commonly searched types of Cuda Developer jobs? The most popular types of Cuda Developer jobs are:
What states have the most Seasonal Cuda Developer jobs? States with the most job openings for Seasonal Cuda Developer jobs include:
Tesla rating
8.5
Based on 669 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 to enhance supply chain processes, including forecasting and optimization algorithms.
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.
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 to enhance supply chain processes, including forecasting and optimization algorithms.
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.