About this role
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:SCTASK1698778
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.