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Internship Graduate Machine Learning Jobs in Missouri

Smithfield Foods

Production OSU Intern

Jamesport, MO

$17.50/hr

... to learning, collaboration, and innovation, Smithfield offers challenging and rewarding careers ... Our internships are typically 10 weeks. Hourly Competitive Starting Pay - $17.50/hour Core ...

Smithfield Foods

Production OSU Intern

Jamesport, MO · On-site

$17.50/hr

... to learning, collaboration, and innovation, Smithfield offers challenging and rewarding careers ... Our internships are typically 10 weeks. Hourly Competitive Starting Pay - $17.50/hour Core ...

Smithfield Foods

Production OSU Intern

Jamesport, MO

$17.50/hr

... to learning, collaboration, and innovation, Smithfield offers challenging and rewarding careers ... Our internships are typically 10 weeks. Hourly Competitive Starting Pay - $17.50/hourCore ...

i.c.stars |*

i.c.stars |* Kansas City

Kansas City, MO · On-site

$14.75 - $19.50/hr

... based learning to build leadership skills and emotional intelligence * core technical skills ... Interns graduate to become *Residents. Residency includes: * 20 months of professional and social ...

i.c.stars |*

i.c.stars |* Kansas City

Kansas City, MO

$14.75 - $19.50/hr

... based learning to build leadership skills and emotional intelligence * core technical skills ... Interns graduate to become *Residents. Residency includes: * 20 months of professional and social ...

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Internship Graduate Machine Learning information

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 key skills and qualifications needed to thrive as an Internship Graduate in 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 are Internship Graduate Machine Learning positions?

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 most commonly searched types of Graduate Machine Learning jobs in Missouri? The most popular types of Graduate Machine Learning jobs in Missouri are:
What are popular job titles related to Internship Graduate Machine Learning jobs in Missouri? For Internship Graduate Machine Learning jobs in Missouri, the most frequently searched job titles are:
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Internship Graduate Machine Learning jobs near you
Postdoctoral Research Associate in AI/Machine Learning

Postdoctoral Research Associate in AI/Machine Learning

Lincoln University of Missouri

Jefferson City, MO • On-site

$50K/yr

Full-time

Re-posted 4 days ago

Job description

PURPOSE:
The Postdoctoral Research Associate in AI/Machine Learning (AI/ML) will lead advanced analytical, AI/ML, and data science components of a USDA-funded forest farming project. The position will develop and apply state-of-the-art AI/ML methods to survey data to improve understanding of farmer behavior, forest farming adoption, and network development, and will contribute to capacity-building, and outreach activities that strengthen data-driven forest farming and agroforestry decision-making at Lincoln University and across Missouri.
ESSENTIAL JOB FUNCTIONS, DUTIES, & RESPONSIBILITIES:
  • List essential job functions, duties & responsibilities for the role. Try to be as detailed as possible.
  • Design, implement, and validate machine learning models (random forests, support vector machines, neural networks) for survey nonresponse, response propensity estimation, and weighting adjustments using statewide farmer, landowner, and stakeholder survey data.
  • Build AI/Natural Language Processing (NLP) pipelines (including large language models) to analyze open-ended survey and focus group data and predict farmer knowledge, attitudes, and adoption willingness.
  • Apply multivariate and dimensionality-reduction techniques (PCA, Kernel-PCA, feature selection) to complex, mixed-type datasets.
  • Integrate quantitative survey data (Likert-scale, categorical, and continuous variables) with qualitative and text-derived features to build predictive models of forest farming adoption, perceived barriers, and support needs among socially disadvantaged and resource-limited farmers.
  • Translate analytical findings into outreach strategies, educational materials, economic analysis inputs, and policy recommendations.
  • Prepare technical documentation, reproducible pipelines, and interpretation reports for technical and non-technical audiences.
  • Develop and deliver educational modules, short courses, and training materials on AI/ML, data science, and cloud-based analytics (Google Cloud, no-code ML tools) for non-coding students, extension professionals, and farmers, with a strong emphasis on agriculture- and agroforestry-relevant applications.
  • Contribute to evaluation metrics and grant deliverables (reports, model portfolios, AI/NLP frameworks, outreach summaries, policy documents).
  • Lead or co-author peer-reviewed papers, conference presentations, and extension publications.
  • Mentor graduate and undergraduate students on survey, qualitative, and data science tasks.

QUALIFICATIONS:
  • List mandatory qualifications.
  • Ph.D. in Statistics, Data Science, Agricultural or Environmental Data Science, Quantitative Social Science, or a closely related field.
  • Experience in developing and applying machine learning models (such as random forests, support vector machines, and neural networks) to empirical datasets.
  • Experience with handling survey or social science data (e.g., Likert scales, categorical responses, mixed methods) and performing statistical modeling or ML-based analysis.
  • Demonstrated competence in at least one major programming language used for data science (R or Python) and in statistical/ML software workflows.
  • Record of peer-reviewed publications.
  • Eligibility to work in the United States for the duration of the appointment.

PREFERRED QUALIFICATIONS:
  • List any preferred / optional qualifications for this role.
  • Prior research experience in agriculture, forestry, agroforestry, environmental science, or related fields, especially projects involving farmers or landowners.
  • Experience applying AI/ML methods to survey data for nonresponse adjustment, propensity weighting, or behavioral prediction.
  • Background in NLP or text analytics, including work with open-ended survey responses, interviews, or focus group transcripts.
  • Experience designing or delivering educational content on AI/ML, data science, or cloud computing (e.g., short courses, workshops, online modules) for non-coding or mixed-expertise audiences.
  • Familiarity with cloud computing platforms (Google Cloud, AWS) for data analysis and ML model deployment, including use of no-code or low-code tools and AutoML services.
  • Demonstrated interest or experience in community-engaged scholarship, extension, or citizen science, especially with underserved or socially disadvantaged farming populations.

PHYSICAL DEMANDS:
  • List physical demands as necessary. If none, describe the environment the employee will be working in, i.e. This position will work in an office environment with minimal exposure to physical work.
  • This position will work primarily in an office environment.
  • Occasional travel may be required for project meetings, workshops, field days, or outreach events at Lincoln University facilities, partner institutions, and community sites across Missouri.

This job description is not intended to be a complete list of all responsibilities, duties or skills required for the job and is subject to review and change at any time, with or without notice, in accordance with the needs of Lincoln University. Since no job description can detail all the duties and responsibilities that may be required from time to time in the performance of a job, duties and responsibilities that may be inherent in a job, reasonably required for its performance, or required due to the changing nature of the job shall also be considered part of the jobholder's responsibility.

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