Artificial Intelligence Intern/Consultant for TxDOT, Austin

Working Title: Artificial Intelligence/Machine Learning Engineer 2 - Intern
State Agency: Texas Department of Transportation
Location: 6230 E Stassney Ln, Austin, TX 78744
Solicitation Reference Number:SSCTASK1698951
Category: Applications/Software Development
Telework Policy: This position requires an onsite presence 4 to 5 days per week. Candidates must reside in the Austin area and be authorized to work in the United States.

Required/Preferred Skill Sets:
3 years, Required - Academic, internship, or entry-level experience in AI, data science, software engineering, or a related field
1 year, Required - Possesses foundational knowledge of common concepts, tools, and practices
1 year, Required - Works under guidance using established processes and standards
1 year, Required - Does not typically exercise independent production decision making
1 year, Required - Coursework toward or completion of a degree in Computer Science, Data Science, Engineering, Mathematics, or related discipline
1 year, Required - Demonstrated interest in artificial intelligence, machine learning, and applied analytics
1 year, Required - Proficiency in Python
1 year, Required - Familiarity with object-oriented programming concepts
1 year, Required - Experience with version control
1 year, Required - Exposure to data analysis, data migration, and basic model development
1 year, Required - Understanding of basic software development and testing concepts
1 year, Preferred - Familiarity with one or more of the following (hands-on or academic):
1 year, Preferred - Data pipelines (e.g., Airflow, Prefect, or cloud-native equivalents)
1 year, Preferred - Model deployment concepts (e.g., REST APIs, serverless patterns)
1 year, Preferred - Cloud platforms or AI services (AWS, Azure, GCP, OCI)
1 year, Preferred - Containerization concepts (Docker)
1 year, Preferred - CI/CD fundamentals
1 year, Preferred - Monitoring or model versioning concepts
1 year, Preferred - Familiarity with OnBase by Hyland, including any OnBase certifications or Hyland training modules completed
1 year, Preferred - Exposure to document management systems or enterprise content management platforms
1 year, Preferred - Experience with Microsoft SQL Server or other relational databases
1 year, Preferred - Knowledge of software development lifecycle (SDLC) and Agile methodologies

Key Attributes for Success
Strong analytical and problem-solving skills
Ability to communicate technical concepts clearly to non-technical audiences
Willingness to learn and adapt in a fast-evolving technical environment
Attention to detail and commitment to data quality
Collaborative mindset and openness to mentorship and feedback

TxDOT work to be accomplished
The AI Apprenticeship Program establishes a sustainable and governed pathway for developing entry-level AI talent in support of TxDOT's AI Strategic Plan. Under supervision, the intern will:
Assist in evaluating emerging AI trends, tools, and vendor solutions against defined business use cases
Contribute to the development of AI/ML models and prototype applications for prioritized use cases
Help design and document data and AI pipelines that integrate with existing systems
Create reports, analyses, and presentations that communicate findings and outcomes clearly
Collaborate with data, engineering, software development, and governance teams

An AI Apprentice will also provide direct support for OnBase team in the following areas:
Assisting in the development, configuration, and deployment of OnBase solutions, including workflows, forms, Unity scripts, and document management.
Collaborating with senior developers and business analysts to understand business requirements and translate them into technical solutions.
Participating in supervised testing, debugging, release validation, and documentation of OnBase applications.
Providing end-user support and training as needed.
Monitoring system performance and supporting intake, initial triage, troubleshooting, documentation, and resolution of routine OnBase tickets.
Maintaining support procedures, knowledge articles, runbooks, and recurring maintenance checklists.
Evaluating low-risk AI use cases that can improve support responsiveness and consistency.