TxDOT work to be accomplished | The Artificial Intelligence (AI) engineer will develop AI/ML proof-of-concept demonstrations and build new AI/ML solutions that scale with TxDOT s pipelines and workflows. The role will be embedded within the Traffic Technology team with the goal to develop AI/ML for Operational Technology that improves the safety and operations of the TxDOT roadway system. The AI engineer will work across teams such as Traffic Technology, ITD AI team, and TRF to gather business requirements, develop AI software, and demonstrate successful solutions to end-users.
**Core Responsibilities**
Gather and document AI solution requirements from business stakeholders.
Develop AI proof-of-concepts and transition successful prototypes into production systems.
Design and implement scalable AI pipelines for enterprise applications.
Train, fine-tune, and validate AI/ML models for optimal performance.
Write clean, efficient software code and scripts for AI workflows.
Conduct rigorous testing and quality assurance of AI models and outputs.
Ensure compliance with organizational IT governance, security, and audit standards.
**Stakeholder Engagement & Communication**
Act as liason between Traffic Technology team, business stakeholders, and automation developers.
Facilitate requirements gathering and ensure clarity in AI solution design.
Communicate progress, risks, and issues to project sponsors and leadership teams. **Delivery Excellence & Governance**
Ensure automation projects comply with TxDOT s IT governance, security, and audit requirements.
Promote reusable components and standardized AI development practices.
Conduct post-implementation reviews to capture lessons learned and improve delivery methods. **Team Coordination & Support**
Collaborate with data engineers, business analysts, and infrastructure teams.
Provide guidance on AI best practices and assist in troubleshooting.
Support knowledge sharing and continuous improvement within the team. |
Minimum Yrs of Experience, Skills, and Qualifications | Python 1-3+ years production experience, this is your primary language
AI/ML Production - Built and deployed 1-3+ ML models serving real users, not just experiments
Cloud Platforms - Experience with AWS, Azure, Google Cloud Platform, or OCI for deploying and managing ML workloads. We leverage AI/ML tools across all major cloud providers (Azure AI, AWS SageMaker/Bedrock, Google Cloud Platform Vertex AI, OCI AI Services) DevOps - Docker and Kubernetes experience
Databases - SQL (PostgreSQL, MySQL) and NoSQL/vector databases
Scripting - Proficient in both Bash and PowerShell for automation
Command Line Interface (CLI) 1-3+ years production experience working in CLI terminal. |
Preferred Skills and Qualifications | CI/CD Experience: Azure DevOps, GitHub Actions, Jenkins, or similar automation pipelines
Computer Vision: Production CV experience with PyTorch/TensorFlow, OpenCV, object detection, segmentation, or real-time inference
Additional Languages: Go or Rust experience for performance-critical components
Feature stores (Feast, Tecton) or advanced feature engineering
Model optimization: quantization, pruning, knowledge distillation
Edge deployment or resource-constrained model deployment
Experiment frameworks for A/B testing ML models
Contributions to open-source ML projects
Real-time streaming data processing (Kafka, Kinesis) |
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