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Internship Graduate Machine Learning Jobs (NOW HIRING)

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

Desired Qualifications * 0-4 years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing-or a strong recent graduate with demonstrated ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

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 ...

NTENT

Machine Learning Engineer

Carlsbad, CA

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 ...

Hive

Machine Learning Manager

Seattle, WA

$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 ...

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Internship Graduate Machine Learning information

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$25.5K

$42.6K

$88K

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

As of Jun 22, 2026, the average yearly pay for internship graduate machine learning 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.

How much do ML interns get paid?

Machine Learning interns typically earn between $15 and $30 per hour, depending on the company, location, and level of experience. Internships often last 10 to 12 weeks and may include additional benefits such as mentorship and skill development opportunities.

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 big 4 internships?

The big 4 internships typically refer to internship programs offered by the four largest professional services firms: Deloitte, PricewaterhouseCoopers (PwC), Ernst & Young (EY), and KPMG. These internships provide opportunities in areas such as audit, consulting, tax, and advisory services, often targeting students pursuing degrees in business, finance, or related fields. They are highly competitive and often include training, mentorship, and potential pathways to full-time employment.

What are the key skills and qualifications needed to thrive as an Internship Graduate in 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 are Internship Graduate Machine Learning positions?

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.

Which 5 jobs will survive AI?

Jobs that require complex human judgment, creativity, emotional intelligence, and specialized skills—such as healthcare professionals, data scientists, software developers, educators, and skilled tradespeople—are more likely to persist despite AI advancements. These roles often involve tasks that are difficult for AI to fully replicate or automate, especially when combined with continuous learning and adaptability.

Is PG in AI worth it?

A postgraduate degree in AI can enhance qualifications for machine learning internship roles by providing advanced knowledge of algorithms, data analysis, and programming skills. It may improve job prospects and salary potential but is not always mandatory, as practical experience and skills in tools like Python and TensorFlow are highly valued in the field.
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Internship Graduate Machine Learning jobs near you
2026 PhD Graduate - Machine Learning and Artificial Intelligence

2026 PhD Graduate - Machine Learning and Artificial Intelligence

Johns Hopkins Applied Physics Laboratory

Laurel, MD • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago

Johns Hopkins Applied Physics Laboratory rating

9.9

Company rating: 9.9 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

1st of 57 rated research

Job description

Description
Do you enjoy exploring and analyzing data to find data-driven solution to complex problems?
Do you want to contribute to work that is crucial to maintaining our national security and strength?
Are you continuously searching for new ways to grow your knowledge and improve your skills?
If you are graduating with a PhD in Statistics, Physics, Mathematics, Computer Science, or a related field, we would love to have you join our team! We are seeking a new PhD graduate with expertise in machine learning to support multi-disciplinary teams performing a variety of quantitative tasks for defense and national security applications. You will be joining a varied team of engineers, software developers, statisticians, data scientists, and analysts who are committed to advancing the state-of-the-art in performance evaluation of the nation's strategic weapons systems throughout their lifecycle. We believe in continually growing our capabilities and cultivating a work environment that embraces innovation, integrity, trust, and teamwork.
As a member of our team, you will...
  • Work with multi-disciplinary teams to support development of data collection, processing, and analysis efforts to assess the performance of a number of systems supporting the Navy and Air Force.
  • Contribute to the full research and development lifecycle for emerging problems. This includes model and algorithm selection, experimentation, analysis, and presentation of results.
  • Apply appropriate statistical and machine learning expertise towards selecting modeling approaches for complex, real-world data.
  • Use internal funding opportunities to shape the direction of future research.
  • Communicate technical knowledge by articulating ideas clearly through papers and presentations to technical staff, management, and government decision makers.

Qualifications
You meet our minimum qualifications for the job if you...
  • Have a PhD in Data Science, Statistics, Physics, Mathematics, Computer Science or a related field.
  • Demonstrate strong interpersonal skills and the ability to work independently and on a team.
  • Have a solid understanding of the mathematical foundations of ML, including probability, statistics, and linear algebra.
  • Have experience using modern AI/ML libraries or frameworks (e.g., PyTorch, TensorFlow, or similar), with including adapting or extending methods for domain-specific problems.
  • Demonstrate experience selecting appropriate modeling techniques for supervised, unsupervised, or reinforcement learning problems in research or real-world settings, with an understanding of when and why they are appropriate.
  • Are able to obtain Interim Secret level security clearance by your start date and can ultimately obtain Top Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

You will go above and beyond our minimum requirements if you...
  • Have experience in project management or leading technical teams.
  • Have experience in writing technical proposals, particularly for government research projects.
  • Have experience mentoring students, teaching, or communicating complex technical concepts in academic, research, or professional settings.
  • Have experience applying machine learning methods to scientific, engineering, or data analysis problems, including areas such as computer vision, NLP, time-series analysis, or scientific machine learning.
  • Have contributed to peer-reviewed publications, technical reports, or presentations in statistics, machine learning, applied mathematics, or related fields.
  • Have experience understanding, developing, or adapting modern AI models and workflows, including large language models, for quantitative analysis and decision support.

About Us
Why Work at APL?
The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.
At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at https://www.jhuapl.edu/careers.
All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact Accessibility@jhuapl.edu.
The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.
Minimum Rate
$105,000 Annually
Maximum Rate
$245,000 Annually

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