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Internship Tesla Machine Learning Engineer Jobs (NOW HIRING)

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

REMOTE Machine Learning Engineer This project-based consulting role invites an experienced Machine Learning Engineer to apply advanced analytical, statistical, and software engineering expertise to ...

We are seeking a Machine Learning Engineer to develop, deploy, and optimize machine learning models and AI solutions. The ideal candidate will have strong experience with Python, machine learning ...

AI/Machine Learning Engineer This project-based consulting role invites an experienced Machine Learning Engineer to apply advanced analytical, statistical, and software engineering expertise to ...

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

About the role: We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex ...

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks NLP Python AZURE Pytorch or tensorflow Machine Learning Engineer / AI Engineer Role Role Overview ...

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Internship Tesla Machine Learning Engineer information

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$25.5K

$42.6K

$88K

How much do internship tesla machine learning engineer jobs pay per year?

As of Sep 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 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 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 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.

What is the difference between Internship Tesla Machine Learning Engineer vs Data Scientist Intern?

AspectInternship Tesla Machine Learning EngineerData Scientist Intern
Required CredentialsRelevant coursework, programming skills, possibly some machine learning knowledgeStatistics, data analysis, programming skills, often some machine learning understanding
Work EnvironmentHands-on projects in AI/ML teams at Tesla, collaborative, fast-pacedData analysis tasks, reporting, modeling in various departments, collaborative
Employer & Industry UsageTesla, automotive, AI, and autonomous driving sectorsVarious 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.

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Infographic showing various Internship Tesla Machine Learning Engineer job openings in the United States as of September 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

Carlsbad, CA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 16 days ago


Job description

Machine Learning Engineer
Position: Full time
Location: Carlsbad office
About Us:
NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search technologies directly into their business-to-consumer offerings. We are a unique group of brilliant minds intent on discovering, learning and building. We work in a vibrant atmosphere, with an emphasis on personal and professional development. This is an opportunity to tackle complex problems usually reserved for a handful of large companies in the search industry.
About the Opportunity:
We are looking for a talented Machine Learning Engineer to join our team and deliver machine learning-driven products. The right candidate will work on development, deployment, and lifecycle management of machine learning models for various large-scale applications (natural language understanding, web search and ranking, recommendation, personalization, dialog/conversation management).
Keywords:
Machine learning, natural language processing, learning-to-rank, online learning, deep learning, interactive machine learning, machine teaching, conversational agents, human computer interaction
Duties and Responsibilities:
  • Design, implement, and deploy machine learning algorithms.
  • Manage machine learning algorithm lifecycle.
  • Coordinate data collection and annotation efforts.
  • Work with real-time data and content coming from various data sources.
  • Manage machine learning data pipelines.
  • Design tests for machine learning algorithm effectiveness and performance monitoring.
  • Design tools and interfaces for interactive machine learning and teaching.
  • Research and development on cutting-edge machine learning technologies.

Qualifications and Skills:
  • Graduate degree in Computer Science with a strong background in machine learning required.
  • Strong problem-solving abilities, solid background in algorithms and data structures required.
  • Strong programming skills in Python and Scala required. Experience in other programming languages (eg. Java, R, Haskell) a plus.
  • Solid knowledge of machine learning tools (eg. scikit-learn, tensorflow, keras, pytorch, Spark MLlib) required.
  • Experience with distributed and streaming data technologies (eg. Hadoop, Spark, Kafka) required.
  • Experience with building and deploying API's with Docker and Kubernetes required.
  • Experience with natural processing tasks (eg. named entity recognition, language modeling, vector representations) required.
  • Experience with Elastic Search, Lucene a plus but not required.
  • Experience with ranking algorithms a plus but not required.
  • Experience with interactive machine learning (eg. active learning, reinforcement learning, machine teaching) a plus but not required.

The ideal candidate will be self-motivated, possess excellent communication skills (both oral and written) and be able to work independently. A keen interest in various aspects of natural language processing is essential in our multi-disciplinary team.
We offer a full comprehensive benefits package including medical, dental and vision. Employees receive a generous time off (PTO) plan and 13 holidays per year. We also offer 401(k) benefits, long term disability benefits and life.