Job Description

This is an onsite position; only local candidates will be considered. The AI/ML Engineer will support the Texas Department of Transportation (TxDOT) on the ITD – BOM Traffic Technology team's AI/ML initiatives. This role develops AI/ML proof-of-concept demonstrations and transitions successful prototypes into production-ready solutions that improve the safety and operations of the TxDOT roadway system. The AI/ML Engineer gathers and documents AI solution requirements from business stakeholders and designs scalable AI pipelines that integrate with TxDOT systems and workflows. This individual trains, fine-tunes, validates, and quality-assures AI/ML models while writing clean, efficient Python code to support reliable AI workflows. The role also serves as a liaison across technical and business teams to communicate progress, risks, and solution-design decisions to project sponsors and leadership. Responsibilities: Gather and document AI solution requirements from business stakeholders. Develop AI/ML proof-of-concept demonstrations and transition successful prototypes into production-ready systems. Design scalable AI pipelines that integrate with TxDOT systems and workflows. Train, fine-tune, validate, test, and quality-assure AI/ML models and outputs. Write clean, efficient Python code and scripts that support reliable AI workflows and production engineering practices. Serve as a liaison between the Traffic Technology team, business stakeholders, the ITD AI team, TRF, and automation developers. Communicate progress, risks, issues, and solution-design decisions to project sponsors and leadership. Ensure AI solutions comply with TxDOT IT governance, security, and audit requirements. Promote reusable components and standardized AI development practices, and conduct post-implementation reviews to capture lessons learned. Collaborate with data engineers, business analysts, and infrastructure teams to provide guidance on AI best practices, troubleshooting support, and knowledge sharing. Requirements Minimum Qualifications: 2 years of experience writing and debugging Python code, developed through coursework, internships, or personal projects. 2 years of exposure to building and training machine learning models using frameworks such as scikit-learn, PyTorch, or TensorFlow through academic, internship, or personal projects. 2 years of familiarity with at least one major cloud provider (AWS, Azure, GCP, or OCI); coursework, sandbox, or free-tier experience is acceptable. 2 years of experience using Git/GitHub for collaborative development. 2 years of working knowledge of SQL. 2 years demonstrating strong analytical and communication skills, with a willingness to learn production engineering practices such as Docker, CI/CD, and cloud deployment on the job. 2 years of basic comfort navigating and running commands in a command line interface (CLI) environment. Preferred Qualifications: 2 years of exposure to Docker or other containerization concepts through coursework or personal projects. 2 years of coursework or personal projects involving computer vision (PyTorch, TensorFlow, OpenCV) or other applied machine learning domains. 2 years of familiarity with Bash or PowerShell scripting for basic automation. 2 years of familiarity with cloud AI services (e.g., Azure AI, AWS SageMaker, GCP Vertex AI) through coursework, certifications, or personal projects. 2 years of exposure to NoSQL or vector databases. A portfolio of academic, capstone, hackathon, or open-source machine learning projects (e.g., a GitHub profile). 2 years of coursework or interest in cloud-based CI/CD pipelines (Azure DevOps, GitHub Actions, or similar). Demonstrated curiosity about applied AI/ML research and current industry tools. 2 years of exposure to data pipelines or streaming concepts (e.g., Kafka) through coursework or projects. Additional Requirements: Candidates must currently reside in the Austin, Texas area. Candidates must be authorized to work in the United States. Work Location and Schedule: Location: TxDOT offices at 6230 E. Stassney Lane, Austin, Texas. Schedule: Monday through Friday, 8:00 AM to 5:00 PM, excluding Texas state holidays. Work Arrangement: Onsite, 4–5 days per week.