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 ...
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 ...
Machine Learning Engineer
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Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...
Machine Learning Engineer
New York, NY · On-site
Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...
Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...
Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...
Machine Learning Engineer
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Required : • 0-4 years of experience (including internships or research) in machine learning ... engineering from experts who will challenge your assumptions. • A self-starter who asks good ...
Machine Learning Engineer
Ann Arbor, MI · On-site
Required : • 0-4 years of experience (including internships or research) in machine learning ... engineering from experts who will challenge your assumptions. • A self-starter who asks good ...
As a Machine Learning Engineer, you will work within a collaborative technical team to build ... internship, personal, or professional projects. - Strong Python foundation and hands-on experience ...
New
As a Machine Learning Engineer, you will work within a collaborative technical team to build ... internship, personal, or professional projects. - Strong Python foundation and hands-on experience ...
New
To be successful you should have 0-3 years of of professional or internship experience in machine learning, data science, or software engineering. Also proficiency in Python and familiarity with ML ...
To be successful you should have 0-3 years of of professional or internship experience in machine learning, data science, or software engineering. Also proficiency in Python and familiarity with ML ...
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South San Francisco, CA · On-site
$35/hr
We are hiring a Machine Learning Engineer Intern to develop novel neural decoders to increase ... Temporary Employees & Interns excluded
Machine Learning Engineer Intern
South San Francisco, CA · On-site
$35/hr
We are hiring a Machine Learning Engineer Intern to develop novel neural decoders to increase ... Temporary Employees & Interns excluded
We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...
Quick apply
We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...
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Machine Learning Engineer
Franklin, WI · On-site
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Austin, TX · On-site
$140K - $180K/yr
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Machine Learning Engineer
Austin, TX · On-site
$140K - $180K/yr
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San Francisco, CA · On-site +1
$172K - $384K/yr
They're now looking for a Machine Learning Engineer to help build the next generation of AI-powered tools that generate structured visuals from scientific inputs . If you're excited by real-world ...
Machine Learning Engineer
San Francisco, CA · On-site +1
$172K - $384K/yr
They're now looking for a Machine Learning Engineer to help build the next generation of AI-powered tools that generate structured visuals from scientific inputs . If you're excited by real-world ...
We seek Machine Learning Engineer | Data Management & Business Intelligence - Predictive Workforce Analytics [NSF0117117] candidates with relevant Government And Public Services Sector Experience ...
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Ann Arbor, MI · On-site
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Machine Learning Engineer
Minneapolis, MN · On-site
We are adding a Machine Learning Engineer to our team! This person will play a key role in designing, implementing, and deploying machine learning models to solve complex problems and enhance our ...
We are adding a Machine Learning Engineer to our team! This person will play a key role in designing, implementing, and deploying machine learning models to solve complex problems and enhance our ...
We are adding a Machine Learning Engineer to our team! This person will play a key role in designing, implementing, and deploying machine learning models to solve complex problems and enhance our ...
Internship Tesla Machine Learning Engineer information
See salary details
$25.5K - $31.2K
5% of jobs
$33.1K is the 25th percentile. Wages below this are outliers.
$31.2K - $36.9K
59% of jobs
$36.9K - $42.5K
9% of jobs
$43K is the 75th percentile. Wages above this are outliers.
$42.5K - $48.2K
17% of jobs
$48.2K - $53.9K
4% of jobs
$53.9K - $59.6K
2% of jobs
$59.6K - $65.3K
3% of jobs
$65.3K - $71K
0% of jobs
$71K - $76.6K
0% of jobs
$76.6K - $82.3K
0% of jobs
$82.3K - $88K
0% of jobs
$25.5K
$42.6K
$88K
How much do internship tesla machine learning engineer jobs pay per year?
As of Jul 13, 2026, the average yearly pay for internship tesla machine learning engineer in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.
What is the difference between Internship Tesla Machine Learning Engineer vs Data Scientist Intern?
| Aspect | Internship Tesla Machine Learning Engineer | Data Scientist Intern |
|---|---|---|
| Required Credentials | Relevant coursework, programming skills, possibly some machine learning knowledge | Statistics, data analysis, programming skills, often some machine learning understanding |
| Work Environment | Hands-on projects in AI/ML teams at Tesla, collaborative, fast-paced | Data analysis tasks, reporting, modeling in various departments, collaborative |
| Employer & Industry Usage | Tesla, automotive, AI, and autonomous driving sectors | Various industries including tech, finance, healthcare, often within data teams |
Both roles involve data and programming skills, but the Tesla Machine Learning Engineer internship focuses more on developing AI/ML models for autonomous systems, while Data Scientist Internships typically emphasize data analysis and insights across different business areas.
What types of projects do Machine Learning Engineer interns at Tesla typically work on, and how much ownership do they have over their work?
Machine Learning Engineer interns at Tesla are often involved in projects that directly contribute to the development of advanced AI systems, such as autonomous driving, predictive analytics, or manufacturing optimization. Interns are typically given meaningful, hands-on tasks and are expected to take significant ownership of specific components or models within a larger project. Collaboration with senior engineers and cross-functional teams is common, providing exposure to Tesla's fast-paced, innovative work culture. Interns also have opportunities to present their work to leadership and receive mentorship, which can be valuable for future career growth.
What does an Internship Tesla Machine Learning Engineer do?
An Internship Tesla Machine Learning Engineer assists in developing and improving machine learning models used in Tesla’s products and operations. Interns typically work on data preprocessing, algorithm development, and model evaluation under the guidance of senior engineers. Their projects may involve computer vision, natural language processing, or predictive analytics applied to Tesla’s vehicles, manufacturing, or autonomous driving systems. The internship offers hands-on experience with real-world data and cutting-edge technology, helping students build valuable industry skills.
What are the key skills and qualifications needed to thrive as an Internship Tesla Machine Learning Engineer, and why are they important?
To thrive as an Internship Tesla Machine Learning Engineer, you need a solid background in computer science, mathematics, and machine learning principles, often supported by progress toward a relevant bachelor’s or master’s degree. Familiarity with Python, TensorFlow or PyTorch, and experience using data processing tools and version control systems are typically required. Strong problem-solving, communication skills, and the ability to collaborate effectively in a fast-paced team environment will set you apart. These skills and qualities are crucial for contributing to high-impact projects and advancing cutting-edge AI solutions at Tesla.
More about Internship Tesla Machine Learning Engineer jobs
What cities are hiring for Internship Tesla Machine Learning Engineer jobs? Cities with the most Internship Tesla Machine Learning Engineer job openings:
What are the most commonly searched types of Tesla Machine Learning Engineer jobs? The most popular types of Tesla Machine Learning Engineer jobs are:
What states have the most Internship Tesla Machine Learning Engineer jobs? States with the most job openings for Internship Tesla Machine Learning Engineer jobs include:
What job categories do people searching Internship Tesla Machine Learning Engineer jobs look for? The top searched job categories for Internship Tesla Machine Learning Engineer jobs are:
- Apple Machine Learning Engineer
- Mlops Machine Learning Engineer
- Machine Learning Research Engineer
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- Machine Learning Hardware
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- Home Based Nvidia Machine Learning
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- Full Time Data Analyst Machine Learning
Full-time
Posted 10 days ago
Tesla rating
8.5
Based on 676 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.