Artificial Intelligence Co-Op/Intern
Job in
Tampa, Hillsborough County, Florida, 33646, USA
Listed on 2026-10-10
Listing for:
The Mosaic Company
Full Time, Apprenticeship/Internship
position Listed on 2026-10-10
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
Where will you work:
Fish Hawk site located at 13830 Circa Crossing Drive, Lithia, FL, 33547. In person, Hybrid. 9/80 schedule if applicable.
Term January 11th, 2027 to April 23th, 2027. Full time Co-Op/Internship. Typically, 36‑40 hours a week.
As an Artificial Intelligence Co‑Op/Intern you will support Mosaic’s AI team in building and scaling AI/ML and GenAI solutions that drive business value across key functions. The role involves rapid prototyping, iterative development, and collaboration with data scientists and engineers to move ideas into production.
Our student opportunities allow you to learn from professionals, offer competitive pay, an opportunity to work with a global leader on exciting projects and much more.
What you’ll do:- Build & Prototype AI Solutions Develop and evaluate ML models, LLM-powered applications, or agentic AI workflows for a scoped business problem Document methodology, assumptions, and trade‑offs while completing a scoped analysis or prototype, then clearly translate results into actionable recommendations.
- Develop Reproducible AI/Data Workflows Build and document reproducible datasets, training pipelines, or evaluation harnesses Define and document cleaning, feature engineering, prompt/evaluation, and validation processes to ensure scalability and reliability, while building reproducible datasets or pipelines.
- Package & Communicate Results Deliver a final package (summary, visuals, code/notebook, model card, runbook) Present key insights, limitations, risks, and recommended next steps to both technical and business stakeholders, and deliver a final package including summaries, visuals, and supporting code or documentation.
- Collaborate across the organization — partnering with data scientists, engineers, product managers, and business stakeholders to scope problems and ship solutions.
- Participation in department meetings and meetings specific to the project assignment.
- Adhering to Mosaic’s mission, guiding principles and priorities, and key competencies.
- Junior level or above by January 2027 pursuing a degree in Computer Science or a closely related field (Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, or Computer/Software Engineering) — Computer Science background strongly preferred
- 2.75 GPA or higher
- Proficiency in Python and familiarity with common libraries (e.g., pandas, Num Py, scikit‑learn, PyTorch or Tensor Flow); comfort with Git and Jupyter notebooks
- Coursework, projects, or hands‑on experience with machine learning, deep learning, NLP, or applied statistics
- Exposure to Generative AI / LLMs (prompting, RAG, agentic workflows) and cloud platforms (Azure, AWS, or GCP) is a strong plus
- Nimble, sharp, and intellectually curious — a fast learner who thrives in ambiguity, asks good questions, and picks up new tools and concepts quickly
- Strong problem‑solving skills and the ability to break down ambiguous business problems into structured, testable AI/data approaches
- 1‑2 years of experience volunteering, working with student/school organizations, or work is preferred. Previous internship or co‑op experience is preferred.
- Reliable transportation and valid driver’s license — You will need to be able to travel to and from sites and/or office.
- Ability to work full timeand be a student in standing at the time of the co‑op/internship
- Selected candidates will be required to successfully complete post‑offer/pre‑placement drug and alcohol screening, background check, physical, functional capacity examination.
- Experience working in a team environment is a must
- Effective verbal and written communication skills — able to explain technical concepts clearly to non‑technical…
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