AI ML Intern Internships
Ai ml intern internships give university students, recent graduates, and early-career switchers hands-on project experience building and deploying machine learning models, mentorship from working engineers and data scientists, and, at many employers, a path toward a full-time offer. Openings are concentrated across Food & Beverage, with TMEIC, Tesla, and TikTok among the employers posting roles now.
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Data Science Intern (AI & Machine Learning)About Sikka.ai Sikka.ai is The Optimizer and Insights Company™, transforming healthcare through AI-powered insights and intelligent automation. Our cloud-based integration platform (Sikka Platform Utility™) connects with thousands of healthcare practices, enabling applications that improve operational efficiency, increase profitability, and enhance patient care.
As a Data Science Intern, you will work alongside AI engineers and data scientists on real-world healthcare AI applications. You'll gain hands-on experience with machine learning, Large Language Models (LLMs), AI agents, and emerging Reinforcement Learning techniques while helping build next-generation intelligent healthcare products.
Responsibilities
- Analyze large-scale healthcare datasets to uncover trends, anomalies, and actionable business insights.
- Build predictive models and data-driven solutions that improve healthcare operations and business performance.
- Perform exploratory data analysis (EDA), statistical analysis, and model evaluation.
- Develop SQL queries and Python pipelines for data extraction, transformation, and analytics.
- Design dashboards and visualizations to communicate insights to technical and business stakeholders.
- Collaborate with engineers and product managers to develop AI-powered healthcare applications.
- Evaluate and improve machine learning and LLM-based systems using quantitative and qualitative metrics.
- Assist in researching and prototyping AI agents, intelligent workflows, and Reinforcement Learning applications for healthcare automation.
- Document experiments, model performance, and technical findings.
Required Qualifications
- Currently pursuing a Master's or Ph.D. in Data Science, Computer Science, Artificial Intelligence, Statistics, Machine Learning, or a related field.
- Strong programming skills in Python and SQL.
- Solid understanding of machine learning fundamentals, including:
- Regression
- Classification
- Clustering
- Feature Engineering
- Model Evaluation Metrics
- Familiarity with statistics and data analysis techniques.
- Basic understanding of Large Language Models (LLMs) and Generative AI.
- Strong analytical thinking, curiosity, and problem-solving skills.
- Excellent written and verbal communication skills.
Preferred Qualifications
- Experience with Reinforcement Learning concepts such as Markov Decision Processes (MDPs), Q-Learning, Policy Gradient methods, PPO, or Deep Reinforcement Learning.
- Familiarity with Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), reward modeling, or preference learning.
- Experience building AI agents using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or similar.
- Experience with Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, and LLM evaluation.
- Familiarity with PyTorch, TensorFlow, Hugging Face, or other deep learning frameworks.
- Experience using cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Personal AI projects, research publications, Kaggle competitions, or open-source contributions are highly desirable.
What You'll Gain
- Work on production AI systems serving real healthcare customers.
- Gain hands-on experience with LLMs, AI Agents, and Reinforcement Learning technologies.
- Collaborate with experienced AI engineers and data scientists in a fast-paced startup environment.
- Build solutions that directly improve healthcare operations and patient experiences.
- Opportunity to contribute to cutting-edge AI products from research through production deployment.
Pay: Up to $25.00 per hour
Location:
- San Jose, CA 95134 (Preferred)
Ability to Commute:
- San Jose, CA 95134 (Required)
Ability to Relocate:
- San Jose, CA 95134: Relocate before starting work (Required)
Work Location: In person
Data Science Intern (AI & Machine Learning)About Sikka.ai Sikka.ai is The Optimizer and Insights Company™, transforming healthcare through AI-powered insights and intelligent automation. Our cloud-based integration platform (Sikka Platform Utility™) connects with thousands of healthcare practices, enabling applications that improve operational efficiency, increase profitability, and enhance patient care.
As a Data Science Intern, you will work alongside AI engineers and data scientists on real-world healthcare AI applications. You'll gain hands-on experience with machine learning, Large Language Models (LLMs), AI agents, and emerging Reinforcement Learning techniques while helping build next-generation intelligent healthcare products.
Responsibilities
- Analyze large-scale healthcare datasets to uncover trends, anomalies, and actionable business insights.
- Build predictive models and data-driven solutions that improve healthcare operations and business performance.
- Perform exploratory data analysis (EDA), statistical analysis, and model evaluation.
- Develop SQL queries and Python pipelines for data extraction, transformation, and analytics.
- Design dashboards and visualizations to communicate insights to technical and business stakeholders.
- Collaborate with engineers and product managers to develop AI-powered healthcare applications.
- Evaluate and improve machine learning and LLM-based systems using quantitative and qualitative metrics.
- Assist in researching and prototyping AI agents, intelligent workflows, and Reinforcement Learning applications for healthcare automation.
- Document experiments, model performance, and technical findings.
Required Qualifications
- Currently pursuing a Master's or Ph.D. in Data Science, Computer Science, Artificial Intelligence, Statistics, Machine Learning, or a related field.
- Strong programming skills in Python and SQL.
- Solid understanding of machine learning fundamentals, including:
- Regression
- Classification
- Clustering
- Feature Engineering
- Model Evaluation Metrics
- Familiarity with statistics and data analysis techniques.
- Basic understanding of Large Language Models (LLMs) and Generative AI.
- Strong analytical thinking, curiosity, and problem-solving skills.
- Excellent written and verbal communication skills.
Preferred Qualifications
- Experience with Reinforcement Learning concepts such as Markov Decision Processes (MDPs), Q-Learning, Policy Gradient methods, PPO, or Deep Reinforcement Learning.
- Familiarity with Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), reward modeling, or preference learning.
- Experience building AI agents using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or similar.
- Experience with Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, and LLM evaluation.
- Familiarity with PyTorch, TensorFlow, Hugging Face, or other deep learning frameworks.
- Experience using cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Personal AI projects, research publications, Kaggle competitions, or open-source contributions are highly desirable.
What You'll Gain
- Work on production AI systems serving real healthcare customers.
- Gain hands-on experience with LLMs, AI Agents, and Reinforcement Learning technologies.
- Collaborate with experienced AI engineers and data scientists in a fast-paced startup environment.
- Build solutions that directly improve healthcare operations and patient experiences.
- Opportunity to contribute to cutting-edge AI products from research through production deployment.
Pay: Up to $25.00 per hour
Location:
- San Jose, CA 95134 (Preferred)
Ability to Commute:
- San Jose, CA 95134 (Required)
Ability to Relocate:
- San Jose, CA 95134: Relocate before starting work (Required)
Work Location: In person
AI ML Intern Internship Market
Who's Hiring
Top Industries Hiring
- Food & Beverage
Tips for Your AI ML Intern Internship Search
Apply in the fall for summer ai ml intern roles
Large technology and research employers open their summer ai ml intern internship pipelines as early as August and September, often closing cohorts before the new year. Smaller companies and co-op programs post closer to start dates. Check listings regularly from late summer onward and apply as soon as a role opens.
Build a public portfolio of complete ML projects
Hiring teams assessing ai ml intern candidates need something concrete to review. Document two or three end-to-end projects on GitHub, including the problem, your approach, the tools and frameworks you used, and the result. A Kaggle competition entry or a linked Colab notebook showing your reasoning is stronger evidence than a list of skills on a resume.
Work your campus network and apply directly at the same time
Campus career fairs surface structured ai ml intern internship programs tied to your university, and your professors and career center staff often know which employers recruit from your school before roles appear publicly. Applying directly to companies running smaller cohorts alongside your campus activity widens the pool you can reach without doubling your effort.
Practice coding and ML concept screens out loud before you apply
Most ai ml intern intern interviews include a technical screen covering data structures, algorithms, and applied ML concepts such as model evaluation, regularization, or probability. Practice explaining your reasoning out loud as you work through problems, since interviewers weigh how you think through a solution as much as whether you reach the right answer.
Target structured ML and research internship programs early
Larger technology companies and research organizations run cohort-based ai ml intern internship programs, including research internships paired with published work, that are built to develop people new to applied ML. These programs recruit early, fill fast, and often move through faculty or university partnerships, so identify the ones that fit your background and apply in the first wave.
Set your work-type filter before you start
On-site roles are 75% of the ai ml intern internships listed here. Decide what you can actually commit to, whether that is on-site, hybrid, or remote, before you start sorting through openings. Filtering by location and work type at the start means you spend your time on roles you can take rather than ones you cannot.
AI ML Intern Internships: Frequently Asked Questions
How do I get an ai ml intern internship?
Lead with coursework and personal projects rather than work history, since hiring teams expect limited experience at the intern level. For ai ml intern candidates, a public GitHub repository with documented ML projects, a Kaggle competition profile, or a linked Jupyter notebook gives recruiters something concrete to assess. Combine direct applications with campus career fairs, where recruiters often move faster for students they meet in person.
Can an ai ml intern internship turn into a full-time job?
Many employers extend return offers to strong interns, but conversion is never guaranteed. For ai ml intern interns, what actually drives it is measurable performance on real project deliverables, whether the team has open headcount at the time offers go out, and how early you communicate your interest in returning. Position for a return offer without counting on one.
When should I apply for ai ml intern internships?
Earlier than most candidates expect. Large tech and finance employers begin recruiting summer ai ml intern interns the preceding fall, often closing cohorts before January. Smaller companies and co-op programs post closer to their start dates, so openings appear year-round. Check listings regularly and apply as soon as a role opens rather than waiting for a season to begin.
Are ai ml intern internships paid?
Most professional ai ml intern internships in the United States are paid. Compensation varies by company size, industry, and location, and ranges from hourly stipends at smaller organizations to competitive weekly pay at large technology and financial services firms. Where an employer discloses compensation, it appears directly in the listing.
What should an ai ml intern internship resume include?
Lead with projects, not work history. List two or three complete, documented ML or data projects, name the tools and frameworks used, and link to the work, such as a GitHub repository, a published Colab notebook, or a Kaggle competition result. Add relevant coursework in machine learning, statistics, or data structures. Keep the resume to one page.
Are there remote ai ml intern internships?
Yes. Remote and hybrid roles make up 25% of the ai ml intern internship listings here, with the rest on-site. Remote cohorts fill fast because they attract applicants from across the country, so apply early and use the work-type filter to see them without sorting through every listing.
What is a machine learning research internship?
Some universities and large technology and research organizations run structured ML research internship programs that pair interns with research scientists on published or productionized work, distinct from engineering-track internships. These programs target students earlier in their academic careers, recruit heavily through faculty referrals and university partnerships, and are competitive, so identifying them and applying in the first recruiting wave matters.
Can international students get ai ml intern internships?
Yes. F-1 students can intern through CPT while enrolled or through OPT work authorization after finishing a degree, and the employer does not have to file anything for either, so many companies are open to international interns. Confirm your eligibility and timing with your university's international student office before accepting an offer.
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