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Artificial Intelligence Machine Learning Internship Jobs

Apple

Machine Learning Engineer, Proactive

Cupertino, CA

$212K - $318K/yr

The AIML Information Intelligence team is creating groundbreaking technology for artificial intelligence, machine learning and natural language processing! The features we create are redefining how ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... Artificial Intelligence (AI)/Machine Learning (ML) models Essential Duties & Responsibilities Research, analyze, support, and implement machine learning solutions on the Snowflake Cloud data ...

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Artificial Intelligence Machine Learning Internship information

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$25.5K

$42.6K

$88K

How much do artificial intelligence machine learning internship jobs pay per year?

As of Jul 2, 2026, the average yearly pay for artificial intelligence machine learning internship 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 are the key skills and qualifications needed to thrive as an Artificial Intelligence Machine Learning Intern, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Intern, you need foundational knowledge in computer science, statistics, and mathematics, often supported by coursework or a degree in a related field. Familiarity with programming languages like Python, machine learning libraries such as TensorFlow or PyTorch, and experience using data analysis tools are typically required. Strong problem-solving abilities, curiosity, and effective communication skills help interns excel in collaborative, fast-paced environments. These skills and qualities are essential to contribute meaningfully to projects, learn quickly, and adapt to evolving technological challenges.

What types of projects can an Artificial Intelligence Machine Learning intern expect to work on during their internship?

As an AI/ML intern, you can expect to work on a variety of projects such as data preprocessing, model development, and performance evaluation. Interns often assist in building and testing machine learning models, analyzing large datasets, and contributing to the improvement of existing algorithms. You may also collaborate closely with data scientists, engineers, and product teams to solve real-world problems and help integrate AI solutions into business processes. These experiences provide valuable exposure to both research and practical applications in the field.

What is the difference between Artificial Intelligence Machine Learning Internship vs Data Science Internship?

AspectArtificial Intelligence Machine Learning InternshipData Science Internship
Required CredentialsBasic programming, math, and AI/ML knowledgeStatistics, programming, and data analysis skills
Work EnvironmentTech companies, research labs, startupsBusiness, finance, healthcare, tech firms
Employer & Industry UsageAI/ML-focused roles in tech and researchData analysis and insights across industries
Search & Comparison IntentUnderstanding AI/ML internship roles and skillsExploring data science internship opportunities

Artificial Intelligence Machine Learning internships focus on developing AI and ML models, requiring programming and math skills. Data Science internships emphasize analyzing data to generate insights, often involving statistics and data visualization. While both roles involve data and programming, AI/ML internships are more specialized in building intelligent systems, whereas Data Science internships focus on interpreting data for decision-making.

What is an Artificial Intelligence Machine Learning Internship?

An Artificial Intelligence (AI) Machine Learning (ML) Internship is a temporary position designed for students or recent graduates to gain hands-on experience in AI and ML fields. Interns work on real-world projects involving data analysis, model development, and the application of machine learning algorithms under the guidance of experienced professionals. These internships help individuals develop practical skills, build a professional network, and improve their understanding of current technologies and tools used in AI and ML. Interns may also participate in research, code reviews, and present their findings. This experience is valuable for pursuing a career in data science, AI engineering, or related fields.
More about Artificial Intelligence Machine Learning Internship jobs
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Artificial Intelligence Machine Learning Internship jobs near you
Infographic showing various Artificial Intelligence Machine Learning Internship job openings in the United States as of June 2026, with employment types broken down into 40% Full Time, 58% Part Time, and 2% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Artificial Intelligence/Machine Learning Oversight Specialist

Artificial Intelligence/Machine Learning Oversight Specialist

Connect Tech+Talent

Austin, TX • On-site, Remote

$17.75 - $23/hr

Other

Posted 7 days ago

Job description

Job Description Artificial Intelligence/Machine Learning Oversight Specialist Austin, Texas (Hybrid or Fully remote) Contract Minimum: 2+ Years - Production software engineering including: Python backend services async pipeline architecture gRPC/REST API development 2+ Years - Demonstrated ability to build, ship, and maintain systems at scale with measurable performance outcomes 2+ Years - Regression testing framework design and execution 2+ Years - Experience building automated test infrastructure that provides coverage across complex multi-system workflows, including systems not accessible via standard DOM or API selectors 2+ Years - High-volume data pipeline validation including batched ingestion, bulk-load integrity verification, record count reconciliation, and exception identification across large structured datasets 1+ Years - Clear technical communication of system behavior, and quality findings to cross-functional teams including engineers, product managers, and non-technical stakeholders in a structured delivery environment Preferred: 2+ Years - PostgreSQL query optimization, bulk-load performance tuning, and data integrity validation at scale; experience identifying and resolving data quality issues across high-volume ingestion and transformation pipelines 1+ Year - Cross-team code review discipline with demonstrated ability to catch API contract issues, performance regressions, and data integrity risks before production; experience reviewing both backend and frontend pull requests across multi-engineer teams 1+ Year - Experience in a production engineering environment requiring end-to-end ownership of quality outcomes across multiple product teams or customer-facing services; comfort operating across ambiguous, fast-moving technical environments with high accountability

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