Artificial Intelligence Engineer

City : Austin

State : Texas

Neos is Seeking an Artificial Intelligence Engineer for a contract role with our client in Austin, TX.

*** ONSITE – ONLY CANDIDATES CURRENTLY RESIDING IN THE AUSTIN, TX AREA WILL BE CONSIDERED***

This role requires onsite work 4-5 days per week at 6230 E Stassney Ln, Austin, TX 78744

No calls, no emails, please respond directly to the “apply” link with your resume and contact details.

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.

• 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.

• Act as liaison 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.

• 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.

• 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.

• Python – 1-3 years production experience.
• AI/ML Production – 1-3 years experience building and deploying ML models serving real users.
• Cloud Platforms – 1-3 years experience with AWS, Azure, Google Cloud Platform, or OCI for deploying and managing ML workloads.
• Dev Ops – 1-3 years experience with Docker and Kubernetes.
• Databases – 1-3 years experience with SQL (Postgre
  
  SQL, MySQL) and No
  
  SQL/vector databases.
• Scripting – 1-3 years experience with Bash and Power Shell automation.
• Command Line Interface (CLI) – 1-3 years production experience working in CLI environments.

• CI/CD – 1 year experience with Azure Dev Ops, Git Hub Actions, Jenkins, or similar pipelines.
• Computer Vision – 1 year production experience with PyTorch, Tensor Flow, OpenCV, object detection, segmentation, or real-time inference.
• Additional Languages – 1 year experience with Go or Rust.
• Feature stores – 1 year experience with Feast, Tecton, or advanced feature engineering.
• Model optimization – 1 year experience with quantization, pruning, or knowledge distillation.
  
  Edge deployment – 1 year experience with resource-constrained model deployment.
• Experiment frameworks – 1 year experience supporting A/B testing of ML models.
• Open-source – Contributions to open-source ML projects.
• Streaming data – 1 year experience with Kafka, Kinesis, or real-time streaming platforms.