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Internship Graduate Machine Learning Jobs (NOW HIRING)

Hive

Machine Learning Manager

San Francisco, CA

$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 ...

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 ...

Apple

Machine Learning Engineer

Austin, TX · On-site

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer ... Qualifications PhD or Graduate degree with research/work experience utilizing data science ...

Hive

Machine Learning Manager

Seattle, WA · 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 ...

Hive

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 ...

Unitytech

Machine Learning Engineer

Bellevue, WA · On-site

$143K - $214K/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 ...

Unitytech

Machine Learning Engineer

Mountain View, CA · On-site

$143K - $214K/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 ...

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site

$143K - $214K/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 ...

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering Preferred Qualifications PhD or Graduate degree with research ...

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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 Jul 12, 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.

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 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.
More about Internship Graduate Machine Learning jobs
What cities are hiring for Internship Graduate Machine Learning jobs? Cities with the most Internship Graduate Machine Learning job openings:
What are the most commonly searched types of Graduate Machine Learning jobs? The most popular types of Graduate Machine Learning jobs are:
What states have the most Internship Graduate Machine Learning jobs? States with the most job openings for Internship Graduate Machine Learning jobs include:
What job categories do people searching Internship Graduate Machine Learning jobs look for? The top searched job categories for Internship Graduate Machine Learning jobs are:
Internship Graduate Machine Learning jobs near you
Infographic showing various Internship Graduate Machine Learning job openings in the United States as of July 2026, with employment types broken down into 3% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, and 2% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Machine Learning Manager

Machine Learning Manager

Hive

San Francisco, CA

$180K - $250K/yr

Full-time

Posted 10 days ago

Job description

About Hive 

Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.

Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!

Machine Learning Manager

In order to execute our vision, we're constantly growing our machine learning team.  We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their full potential.  We value hard workers who have no qualms working with terabyte-scale datasets. We're interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects of a massive scale, contributes innovative ideas and ingenious modeling improvement strategies to the team, and is capable of mentoring junior engineers through their journey to become better.
Responsibilities
  • Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
  • Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
  • Participate in products technical design and architecture
  • Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production
  • Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
  • Implement and manage security protocols such as training, code review, and best practices
  • Own and manage the risk and security of your business function in coordination with the Security Team
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority
Requirements
  • 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 working with real world data
  • Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
  • 2+ years experience managing machine learning teams
  • You have an ability to understand and make well-reasoned tradeoffs in designing features
  • Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
  • Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
  • Have experience collaborating with product managers and labeling team in delivering model improvements
Who We Are

We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.

Thank you for your interest in Hive and we hope to meet you soon!

The current expected base salary for this position ranges from $180,000 - $250,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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