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Machine Learning Developer Intern Jobs (NOW HIRING)

Spotify

Machine Learning Engineer

They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners. Responsibilities : • ...

Spotify

Machine Learning Engineer

Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

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 ...

Qeexo, Co.

Data Engineering Intern

San Clemente, CA · On-site

$25/hr

As a pioneer in automated machine learning for edge devices and a subsidiary of TDK Corporation, a ... The Data Engineering Intern supports the development of scalable data systems and infrastructure ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

Qeexo, Co.

Data Engineering Intern

San Clemente, CA

$25/hr

As a pioneer in automated machine learning for edge devices and a subsidiary of TDK Corporation, a ... The Data Engineering Intern supports the development of scalable data systems and infrastructure ...

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Machine Learning Developer Intern information

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$25.5K

$42.6K

$88K

How much do machine learning developer intern jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning developer intern 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 do Machine Learning Developer Interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What does a Machine Learning Developer Intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

What are the key skills and qualifications needed to thrive as a Machine Learning Developer Intern, and why are they important?

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities are hiring for Machine Learning Developer Intern jobs? Cities with the most Machine Learning Developer Intern job openings:
What states have the most Machine Learning Developer Intern jobs? States with the most job openings for Machine Learning Developer Intern jobs include:
Machine Learning Developer Intern jobs near you

Machine Learning Engineer

Spotify

Remote

Full-time

Re-posted 26 days ago

Job description

Job Summary:
Spotify is a leading audio streaming subscription service that aims to unlock the potential of human creativity. They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners.
Responsibilities:
• Contribute to the design, build, evaluation, shipping, and refinement of systems that improve Spotify’s promotional performance with hands-on ML development
• Collaborate with a multidisciplinary team to optimize machine learning models for production use cases, ensuring they are highly efficient, scalable, and consistently meet well-defined success criteria
• Influence the technical design, architecture, and infrastructure decisions to support new and diverse machine learning architectures.
• Work with Data and ML Engineers to support transitioning machine learning models from research and development into production
• Implement and monitor model success metrics, diagnose issues, and contribute to an on-call schedule to maintain production stability.
Qualifications:
Required:
• Experience implementing ML systems at scale in Java, Scala, Python or similar languages
• Experience with ML frameworks such as TensorFlow, PyTorch, etc.
• Understanding of how to bring machine learning models from research to production
• Collaborative mindset, enjoy working closely with research scientists, machine learning engineers, and data engineers
• Experience in optimizing machine learning models for production use cases
• Familiarity with creating model success metric dashboards
• Willingness to take part in an on-call schedule to maintain performance
Preferred:
• Experience with data pipeline tools like Apache Beam, Scio
• Experience with cloud platforms like GCP
• Exposure to causal ML models, including things like counterfactuals
Company:
Spotify is a commercial music streaming service that provides restricted digital content from a range of record labels and artists. Founded in 2006, the company is headquartered in Stockholm, SWE, with a team of 5001-10000 employees. The company is currently Late Stage.

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