AI Engineering Intern

constelliscareers; United States; On-site; USD 34,000 - 48,000; Part time

Job summary

Constellis is offering an AI Engineering Intern role designed to give hands-on experience in building and evaluating machine learning, generative AI, and data science solutions for enterprise use cases. You will work on AI workflow automation, model evaluation, retrieval-augmented generation, and secure AI development under guidance from the AI Transformation team.

Ideal candidates are pursuing degrees in CS/DS/AI/ML and have practical Python experience with pandas, NumPy, scikit-learn, PyTorch,

Qualifications

• Enrolled in graduate or undergraduate degree in CS/DS/AI/ML or related field.
• Coursework in ML, data mining, NLP, generative AI, or analytics.
• Experience with Python and data science libraries (pandas, NumPy, scikit-learn, PyTorch, TensorFlow).
• Familiarity with SQL, data pipelines, APIs, cloud services, and version control.
• Strong analytical, communication, and documentation skills.

Responsibilities

• Develop ML models and AI prototypes for enterprise use cases.
• Prepare data, engineer features, and monitor model performance.
• Work on generative AI and retrieval-augmented generation experiments.
• Evaluate model quality, grounded-answer accuracy, bias, and reliability.
• Create scripts, notebooks, docs, dashboards to communicate results.
• Collaborate with IT, AI Transformation, data stewards and teams to translate problems into AI solutions.
• Work hours are Mon-Fri core hours with possible extended hours.
• Other duties as assigned.

Skills

Analytical skills

Problem-solving

Communication

Documentation

Education

Relevant technical degree (CS/Data Science/AI/ML)

Tools

Python

Pandas

NumPy

scikit-learn

PyTorch

TensorFlow

LangChain

SQL

APIs

GitHub

Notebooks

Job description

POSITION SUMMARY

The AI Engineering Intern will support Constellis’ Enterprise AI Transformation initiatives by assisting with the design, development, evaluation, and deployment of machine learning, generative AI, and data science solutions. This graduate-level internship will provide hands-on experience working with enterprise data, AI workflow automation, model evaluation, retrieval-augmented generation, analytics, and secure AI application development in support of business, compliance, and operational use cases.

RESPONSIBILITIES

• Assist in developing machine learning models, data science workflows, and AI-enabled prototypes that support enterprise use cases across business functions.
• Support data preparation, feature engineering, exploratory analysis, model training, testing, validation, and performance monitoring activities.
• Contribute to generative AI, retrieval-augmented generation, and agentic workflow experiments using approved enterprise platforms, data sources, and development practices.
• Assist with evaluation of model quality, grounded-answer accuracy, task success, hallucination risk, bias, explainability, and operational reliability.
• Develop reusable scripts, notebooks, documentation, dashboards, and technical summaries to communicate findings, assumptions, results, and recommendations.
• Collaborate with Information Technology, AI Enterprise Transformation, business stakeholders, data stewards, and application teams to translate business problems into practical AI and analytics solutions.
• Work is typically based in a busy office environment and subject to frequent interruptions. Business work hours are Monday-Friday standard core hours; however, some extended hours may be required based on project needs.
• Other duties as assigned.

QUALIFICATIONS

• Currently enrolled in a graduate or undergraduate degree program in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, Engineering, Economics, or a related technical field.
• Coursework or project experience in machine learning, statistical modeling, deep learning, natural language processing, generative AI, data mining, optimization, or predictive analytics.
• Experience with Python and common data science libraries such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow, LangChain, or similar tools.
• Familiarity with SQL, data pipelines, APIs, cloud services, version control, notebooks, model evaluation, and responsible AI concepts.
• Strong analytical, problem-solving, communication, and documentation skills with the ability to explain technical findings to both technical and non-technical stakeholders.
• Desired experience includes Azure, Microsoft 365 Copilot, Copilot Studio, Power Platform, SharePoint, GitHub, DevOps practices, retrieval-augmented generation, vector databases, model monitoring, or MLOps.
• Must be able to protect sensitive company information and follow all applicable information security, data handling, privacy, and acceptable-use requirements.
• Ability to work in an office environment, use a computer for extended periods, communicate effectively in meetings, and perform standard internship duties with or without reasonable accommodation.