The Role
Develop AI/ML proof-of-concepts and transition successful prototypes into production systems for roadway safety and operations. Responsibilities include gathering requirements, designing scalable AI pipelines, training and validating models, writing Python code, ensuring governance and security compliance, and collaborating with technical and business stakeholders. The role also communicates project risks and progress, supports troubleshooting, promotes reusable development practices, and contributes to post-implementation reviews.
Summary Generated by Built In
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.
Skills Required
- Two years of experience writing and debugging Python code through coursework, internships, or personal projects.
- Two years of experience building and training machine learning models using scikit-learn, PyTorch, TensorFlow, or similar frameworks.
- Two years of familiarity with a major cloud provider: AWS, Azure, GCP, or OCI.
- Two years of experience using Git or GitHub for collaborative development.
- Two years of working knowledge of SQL.
- Two years demonstrating strong analytical and communication skills, with willingness to learn Docker, CI/CD, and cloud deployment.
- Two years of basic comfort navigating and running commands in a command-line interface.
- Two years of exposure to Docker or other containerization concepts.
- Two years of coursework or personal projects involving computer vision or other applied machine learning domains.
- Two years of familiarity with Bash or PowerShell scripting.
- Two years of familiarity with cloud AI services such as Azure AI, AWS SageMaker, or GCP Vertex AI.
- Two years of exposure to NoSQL or vector databases.
- Portfolio of academic, capstone, hackathon, or open-source machine learning projects.
- Two years of coursework or interest in cloud-based CI/CD pipelines such as Azure DevOps or GitHub Actions.
- Demonstrated curiosity about applied AI/ML research and current industry tools.
- Two years of exposure to data pipelines or streaming concepts such as Kafka.
- Currently residing in the Austin, Texas area.
- Authorized to work in the United States.
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The Company
What We Do
Air InfoSec is a veteran-owned and led cybersecurity consulting and staffing firm based in Austin, Texas, focused on enhancing government security through expert staff placement.
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