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Internship Tesla Machine Learning Engineer Jobs in Canton, MA

Lead Machine Learning Engineer

Cambridge, MA

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

About the position: We're looking for a Senior Machine Learning Engineer with deep expertise in some area of ML engineering to join our growing ML team and work closely with our software and computer ...

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from ...

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from ...

Senior Machine Learning Engineer

Boston, MA · On-site

$133K - $175K/yr

The Crown Is Yours As a Senior Machine Learning Engineer, you'll design, implement, and scale production-grade data and machine learning pipelines that drive measurable business outcomes. You'll ...

Showing results 41-60

Internship Tesla Machine Learning Engineer information

See Canton, MA salary details

$27K

$45K

$93.1K

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

As of Aug 9, 2026, the average yearly pay for internship tesla machine learning engineer in Canton, MA is $45,028.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,400.00 and $48,600.00 per year, depending on experience, location, and employer.

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.

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.
Infographic showing various Internship Tesla Machine Learning Engineer job openings in Canton, MA as of June 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $45,028 per year, or $21.6 per hour.

Machine Learning Engineer - Computational Drug Discovery

4:59 NewCo, a 5AM Ventures Company

Watertown, MA • On-site

Full-time

Re-posted 4 days ago


Job description

Job Summary:
4:59 NewCo, a 5AM Ventures Company, is focused on developing a pipeline of small molecules to address unmet clinical needs. The Machine Learning Engineer will work at the intersection of machine learning research and experimental teams, ensuring that models transition from research to production effectively.
Responsibilities:
• Own and maintain production machine learning infrastructure, ensuring models developed by the research team are robust, maintainable, and deployable
• Develop computational tools, data pipelines, and machine learning systems that support scientific workflows across chemistry and biology
• Collaborate closely with chemists and biologists to understand requirements and translate them into effective software solutions
• Design and build internal AI agents and automation systems, with substantial opportunity to define both the technical direction and user experience
• Write clean, well-tested, version-controlled code and contribute to a strong engineering culture through code review and technical collaboration
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Chemistry, Physics, Data Science, or a related technical field
• Strong software engineering fundamentals, including code quality, testing, version control, and CI/CD practices
• Hands-on experience developing machine learning systems using PyTorch
• Familiarity with undergraduate-level organic chemistry; you do not need to be a chemist, but should be comfortable working with molecular structures and chemical concepts
• Ability to communicate effectively with scientific collaborators from non-programming backgrounds
• Strong sense of ownership and the ability to independently drive ambiguous projects from concept to completion
• We are particularly excited to bring in people who enjoy turning research ideas into tools that scientists actually use. The ideal candidate is comfortable operating across disciplines, takes pride in building reliable systems, and appreciates the opportunity to have a direct impact on scientific decision-making.
Preferred:
• Experience with AWS, MLflow, SQL, Polars, pandas, Ray, or scikit-learn
• Familiarity with LLM tooling, AI agents, or agent development frameworks
• Background in cheminformatics, computational biology, bioinformatics, or related fields
• Experience working in a startup, research, or other highly iterative technical environment
Company:
4:59 is a hands-on internal effort of 5AM Ventures to discover, incubate, and fund breakthrough science. Founded in , the company is headquartered in Boston, MA, US, , with a team of 11-50 employees. The company is currently Early Stage.