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Machine Learning Ai Intern Jobs (NOW HIRING)

SWBC

AI Intern

San Antonio, TX

$13.50 - $18/hr

... machine learningsolutions. This internship will focus on building AI-powered applications and ... As an SWBC intern, you will be learning on the job in real-time from talented professionals within ...

By Light Professional IT Services LLC

AI Intern

As an Intern, you will have the opportunity to work on a cutting-edge project that involves ... Familiarity with machine learning or data science concepts and experience with data visualization ...

Microsoft AI

Machine Learning

Mountain View, CA · On-site

Microsoft AI is a part of Microsoft focused on pushing the boundaries of AI towards Humanist ... Preferred : • Doctorate in Computer Science, Machine Learning, Human-Centered AI or related field ...

Steel Partners

AI Intern

$15.25 - $20.75/hr

Together, these pillars create a culture focused on long-term success, accountability, learning ... The Role The Artificial Intelligence (AI) Intern will be embedded across Steel Partners' corporate ...

Bert Black

AI Intern

Little Rock, AR · On-site

$11/hr

As the AI Intern at Bert Black Service Companies, you'll be helping create your own role. This is a self-driven, hands-on role for someone who's excited to apply AI in ways that actually move the ...

Rivian

Machine Learning/AI Engineer

Palo Alto, CA · On-site

$139K - $155K/yr

... aware AI. Hands-on experience with quantized model deployment, ML design stacks, and code ... Experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and their low-level IRs or ...

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All JobsMachine Learning Ai Intern Jobs

Machine Learning Ai Intern information

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$25.5K

$42.6K

$88K

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

As of Jun 21, 2026, the average yearly pay for machine learning ai 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.

What does a Machine Learning AI Intern do?

A Machine Learning AI Intern assists in developing, testing, and deploying machine learning models and algorithms under the supervision of experienced data scientists or engineers. Typical responsibilities include data preprocessing, feature engineering, model evaluation, and documentation. Interns may also help in researching new AI techniques and supporting the integration of models into existing applications. The role provides hands-on experience with machine learning tools, programming languages like Python, and frameworks such as TensorFlow or PyTorch. This internship helps build foundational skills for a career in artificial intelligence and data science.

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

To thrive as a Machine Learning AI Intern, you need a solid foundation in mathematics, programming (often Python), and machine learning concepts, usually supported by coursework or relevant projects. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Curiosity, problem-solving ability, and strong communication skills help interns collaborate effectively and learn quickly in dynamic environments. These skills are crucial for contributing meaningfully to projects, adapting to new technologies, and growing within the fast-evolving AI field.

What types of projects do Machine Learning AI Interns typically work on during their internship?

As a Machine Learning AI Intern, you can expect to work on real-world projects such as developing predictive models, performing data preprocessing and analysis, or contributing to the improvement of existing algorithms. Interns often assist with tasks like data cleaning, feature engineering, and model evaluation, while collaborating closely with data scientists and engineers. This hands-on experience helps interns build practical skills and gain exposure to the entire machine learning workflow in a professional setting.

What is the difference between Machine Learning Ai Intern vs Data Science Intern?

AspectMachine Learning Ai InternData Science Intern
Required CredentialsRelevant coursework, programming skills, basic understanding of ML conceptsStatistics, programming, data analysis skills, often with similar educational background
Work EnvironmentTech companies, startups, research labs focusing on AI/ML projectsVariety of industries including finance, healthcare, tech, focusing on data analysis
Employer & Industry UsagePrimarily in AI/ML development teams within tech and research sectorsAcross industries for data analysis, reporting, and decision-making support

Machine Learning Ai Interns focus on developing and applying AI and ML models, often working closely with data scientists and engineers. Data Science Interns work on analyzing data, creating reports, and supporting data-driven decisions. While both roles require programming and analytical skills, ML Interns typically specialize in AI algorithms, whereas Data Science Interns focus on broader data analysis tasks.

What cities are hiring for Machine Learning Ai Intern jobs? Cities with the most Machine Learning Ai Intern job openings:
What states have the most Machine Learning Ai Intern jobs? States with the most job openings for Machine Learning Ai Intern jobs include:
Machine Learning Ai Intern jobs near you
AI/Machine Learning Engineering - Intern

AI/Machine Learning Engineering - Intern

DataVisor

Mountain View, CA • On-site

$25 - $70/hr

Contractor

Posted 12 hours ago

Job description

About DataVisor
DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!
Role Summary
We are seeking highly motivated, soon-to-graduate MS or Ph.D. students in Computer Science, Machine Learning, Data Science, or related fields to join us as AI / ML Engineering Interns.
This internship is ideal for candidates who are eager to learn how large-scale AI systems are built and deployed in production. You will work closely with experienced engineers and data scientists to help build the Intelligence Layer and Data Consortium that power DataVisor's real-time fraud detection platform.
This internship focuses on distributed systems, data pipelines, machine learning infrastructure, and applied AI, including exposure to agentic flows and large language models (LLMs).
What You'll Do
  • Data Engineering & Pipelines
    • Assist in building and maintaining high-throughput data pipelines using technologies such as Spark, Kafka, or Flink
    • Help process and aggregate real-time signals (e.g., device fingerprints, behavioral data) into shared intelligence systems
  • Distributed Systems & Scalability
    • Learn to design and optimize backend systems that support large-scale, real-time decisioning
    • Contribute to improving system performance, reliability, and latency under high transaction volumes
  • AI Applications & Agentic Flows
    • Support the development of AI applications and agentic workflows using state-of-the-art LLMs (e.g., OpenAI, Anthropic, Google)
    • Experiment with natural language interfaces, intelligent rule suggestions, and automated strategy generation
  • Machine Learning Pipelines
    • Help deploy and monitor pipelines for unsupervised and supervised ML models
    • Assist with integrating models into real-time scoring APIs and decision engines
  • Privacy & Security
    • Learn best practices for privacy-first system design, including tokenization and hashing to protect sensitive data
  • Cross-Functional Collaboration
    • Work alongside Data Science, Product, and Engineering teams to test ideas, validate models, and ship production features

Requirements
  • Current MS or Ph.D. students majoring in Computer Science, Machine Learning, AI, Data Science, or a related field
  • Passionate about learning how real-world AI systems are built at scale
  • Comfortable working with complex technical problems and eager to grow through mentorship
  • Strong programming skills in Python
  • Familiarity with at least one of the following: distributed systems, machine learning, data engineering, or backend development
  • Academic or project experience with big data frameworks (Spark, Kafka, Flink) is a plus
  • Understanding of core ML concepts (supervised / unsupervised learning)
Preferred (Nice-to-Have)
  • Coursework or project experience with:
    • LLMs, RAG architectures, LangChain, or vector databases
    • Cloud platforms (AWS) and containers (Docker)
    • Stream processing or real-time systems
  • Interest in fraud, risk, or security domains (not required)

Benefits
  • Hands-on experience working on production-scale AI systems
  • Mentorship from senior engineers and data scientists
  • Exposure to cutting-edge agentic AI and LLM applications
  • Opportunity for full-time conversion based on performance and business needs
  • Comp Range, $25 - $70/hour

Apply