ZipRecruiter

Log In

1

Internship Graduate Machine Learning Jobs in Missouri

Veeda AI

Internship - Veeda AI Scientist

California, MO · On-site

$120 - $180/hr

You have a solid understanding of machine learning fundamentals and modern deep learning methods -- optimization, generalization, architectures, and the intuition to know when theory breaks down in ...

Fellowship of Christian Athletes

Intern

Kansas City, MO

$14.75 - $19.50/hr

FCA Interns are collegiate volunteers who engage through FCA in a learning and developmental ... Current Georgia State University student-athlete or graduate assistant * Strong Christian faith and ...

Varsity Tutors

Data Science Tutor

Kansas City, MO · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ... graduate programs. * Conceptual Teaching & Problem-Solving: Skilled at teaching the full data ...

Varsity Tutors

Data Science Tutor

Saint Louis, MO · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ... graduate programs. * Conceptual Teaching & Problem-Solving: Skilled at teaching the full data ...

Varsity Tutors

Data Science Tutor

Columbia, MO · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ... graduate programs. * Conceptual Teaching & Problem-Solving: Skilled at teaching the full data ...

previous page

Showing results 41-60

All JobsGraduate Machine Learning JobsInternship Graduate Machine Learning JobsInternship Graduate Machine Learning Jobs in Missouri

Internship Graduate Machine Learning information

What is an internship graduate machine learning?

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.

What are the key skills and qualifications needed to thrive as an internship graduate 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 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 most commonly searched types of Graduate Machine Learning jobs in Missouri?

The most popular types of Graduate Machine Learning jobs in Missouri are:

What cities in Missouri are hiring for Internship Graduate Machine Learning jobs?

Cities in Missouri with the most Internship Graduate Machine Learning job openings:

Internship Graduate Machine Learning jobs near you
Infographic showing various Internship Graduate Machine Learning job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Internship - Veeda AI Scientist

Veeda AI

California, MO • On-site

$120 - $180/hr

Other

Posted 4 days ago

Job description

About US

Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one.


Responsibilities

  • Product-Driven Research: Push the frontier on generative world models.


  • Foundation Models: Advance image, video, and 3D generation architectures. You will design, train, and iterate on the core models that power creation pipeline across modalities.


  • Post-Training: Develop RLHF, DPO, reward modeling, and alignment techniques that give creators fine-grained control over aesthetics, anatomy correctness, and stylistic consistency.


  • Data Curation at Scale: Build and refine large-scale data pipelines — sourcing, filtering, labeling.



Requirements

  • You have a Bachelor's degree or equivalent hands‑on experience in Computer Science, Engineering, or a related technical field.


  • You have a solid understanding of machine learning fundamentals and modern deep learning methods — optimization, generalization, architectures, and the intuition to know when theory breaks down in practice.



Nice to Have

  • You have built or maintained scalable data curation pipelines for ML training data.


  • You have published or contributed to research on generative models for image, video, or 3D content.


  • You have contributed to open-source generative model projects or related infrastructure.


#J-18808-Ljbffr

Apply