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Internship Graduate Machine Learning Jobs in Mountain View, CA

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems. You'll help build and ...

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems. You'll help build and ...

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Internship Graduate Machine Learning information

See Mountain View, CA salary details

$30.1K

$50.2K

$103.8K

How much do internship graduate machine learning jobs pay per year?

As of Aug 8, 2026, the average yearly pay for internship graduate machine learning in Mountain View, CA is $50,235.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,300.00 and $54,300.00 per year, depending on experience, location, and employer.

What is the difference between Internship Graduate Machine Learning vs Data Analyst?

AspectInternship Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; basic knowledge of programming and statisticsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentTech companies, research labs, startups; project-based, collaborative teamsBusiness, finance, marketing sectors; focus on reporting and data interpretation
Employer & Industry UsageUsed in tech, AI, and research industries for developing machine learning modelsCommon in corporate, finance, and consulting firms for data-driven decision making

While both roles involve working with data, an Internship Graduate Machine Learning focuses on developing algorithms and models using programming skills, often in tech environments. In contrast, a Data Analyst emphasizes interpreting data, creating reports, and supporting business decisions. The roles overlap in data handling but differ in technical depth and application focus.

What are the key skills and qualifications needed to thrive as an internship graduate machine learning, and why are they important?

To thrive as an Internship Graduate in Machine Learning, you typically need a strong background in mathematics, programming (especially Python), and familiarity with algorithms and data structures, often supported by coursework or a degree in computer science, statistics, or a related field. Hands-on experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of tools such as Jupyter Notebooks and version control systems like Git, are highly valued. Curiosity, problem-solving, teamwork, and effective communication are crucial soft skills to excel in collaborative and innovative environments. These competencies enable interns to contribute to real-world projects, adapt to fast-changing technologies, and communicate findings clearly within interdisciplinary teams.

What is an internship graduate machine learning?

Internship Graduate Machine Learning positions are entry-level roles designed for recent graduates or students who have completed coursework in machine learning, data science, or related fields. These internships provide hands-on experience working with real-world data, building and testing machine learning models, and collaborating with experienced professionals. Interns gain exposure to industry-standard tools and techniques, helping them bridge the gap between academic learning and practical application. Such positions are valuable for building a portfolio, networking, and enhancing job prospects in the rapidly growing field of artificial intelligence.

What types of projects do internship graduate machine learning roles typically involve, and how are responsibilities structured within the team?

Internship Graduate Machine Learning roles often focus on supporting ongoing research or development projects, such as building predictive models, cleaning and analyzing data, or prototyping algorithms. Interns usually collaborate closely with data scientists and engineers, contributing to specific project milestones while learning best practices in model development and deployment. Responsibilities are often structured to allow for mentorship and feedback, with interns participating in regular team meetings, code reviews, and brainstorming sessions. This collaborative environment provides valuable exposure to real-world machine learning workflows and helps interns build both technical and soft skills relevant to the field.
What are popular job titles related to Internship Graduate Machine Learning jobs in Mountain View, CA? For Internship Graduate Machine Learning jobs in Mountain View, CA, the most frequently searched job titles are:
What job categories do people searching Internship Graduate Machine Learning jobs in Mountain View, CA look for? The top searched job categories for Internship Graduate Machine Learning jobs in Mountain View, CA are:
What cities near Mountain View, CA are hiring for Internship Graduate Machine Learning jobs? Cities near Mountain View, CA with the most Internship Graduate Machine Learning job openings:

Machine Learning Physics Graduate Student

LLNL

Livermore, CA

$6.7K - $8.2K/mo

Full-time

Retirement

Re-posted 6 days ago


Job description

Company Description

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. 

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

Job Description

We have multiple openings for Machine Learning Graduate Student Interns to engage in practical research experience to further their educational goals. You will work on multidisciplinary projects, such as development of classical empirical and machine learning interatomic potentials, discovery of partial differential equations (PDEs), numerical solutions of partial differential equations to model material behavior at continuum scale and analysis of large atomic datasets. These positions are in in the Equation of State Materials Theory Group of the Physics Division of the Physical & Life Sciences Directorate.

This position requires full-time on-site presence due to the nature of the work.

You will 

  • Develop parallel C/C++/Python codes to train, test and evolve (a) PDEs (for phase field and phase field crystal models) discovered from data, and (b) interatomic potentials developed from quantum simulations.
  • Explore the use of machine learning methods to discover and evolve PDEs for phase field and phase field crystal models.
  • Analyze results, provide weekly updates and present work at poster sessions
  • Review literature in the field of study, document results and write papers.
  • Perform other duties as assigned.
Qualifications
  • Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA).  See Additional Information section below for details.
  • Continuing student in good standing at an accredited institution of higher education pursuing a graduate degree in Physics or related field.
  • Research background with a record of publication.
  • Experience in writing codes (in C/C++ and Python) and a background in Materials Science/Engineering/Physics/Applied Mathematics.
  • Excellent skills in written and verbal communication, as well as teamwork.

Qualifications We Desire

  • Experience in parallel computing, porting codes to GPUs, experience in numerical solutions of partial differential equations.

Pay Range

$6,752 - $8,201 Monthly 

This position is under a step structure.  Please note that the step placement is determined by your most recent completed academic year.

Additional Information

#LI-Onsite

Why Lawrence Livermore National Laboratory?

  • Included in 2026 Best Places to Work by Glassdoor!
  • Holiday Pay
  • Sick leave accrual
  • Individual 401(k) contributions
  • Our values - visit https://www.llnl.gov/inclusion/our-values 

Security Clearance

None required.  However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process.  This process includes completing an online background investigation form and receiving approval of the background check.  

National Defense Authorization Act (NDAA)

The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities.  The restrictions of NDAA Section 3112 apply to this position.  To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112.

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under "Find Your Job" of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.