Artificial Intelligence Engineer
# Artificial Intelligence Engineer **VA Simplified** · Austin, TX 78789 · `On-site` 🕒 **Статус:** *Опубликовано: 5 дней назад* · *Источник: Indeed* --- ### About the Role Job Description 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 YEARS OF EXCPERIENCE SKILL & QUALIFICATION --- Python – comfortable writing and debugging Python code, developed through coursework, internships, or personal projects --- Machine Learning Fundamentals - Exposure to building and training ML models using frameworks such as scikit-learn, PyTorch, or TensorFlow (academic, internship, or personal projects) --- Cloud Platforms - Familiarity with at least one major cloud provider (AWS, Azure, GCP, or OCI); coursework, sandbox, or free-tier experience is acceptable Version Control - Experience using Git/GitHub for collaborative development --- Databases - Working knowledge of SQL --- Communication & Problem-Solving - Strong analytical skills and a demonstrated willingness to learn production engineering practices (Docker, CI/CD, cloud deployment) on the job --- Command Line Interface (CLI) - Basic comfort navigating and running commands in a terminal environment PREFERRED SKILLS & QUALIFICATION --- Exposure to Docker or other containerization concepts through coursework or personal projects --- Coursework or personal projects involving computer vision (PyTorch/TensorFlow, OpenCV) or other applied ML domains --- Familiarity with Bash or PowerShell scripting for basic automation --- Familiarity with cloud AI services (e.g., Azure AI, AWS SageMaker, GCP Vertex AI) through coursework, certifications, or personal projects --- Exposure to NoSQL or vector databases --- A portfolio of academic, capstone, hackathon, or open-source ML projects (e.g., a GitHub profile) --- Coursework or interest in cloud-based CI/CD pipelines (Azure DevOps, GitHub Actions, or similar) --- Curiosity about applied AI/ML research and current industry tools --- Exposure to data pipelines or streaming concepts (e.g., Kafka) through coursework or projects Pay: $33.00 - $38.00 per hour Expected hours: No more than 33.0 per week Benefits: 401(k) 401(k) matching Dental insurance Work Location: In person
Наблюдалась 2026-09-21, впервые 2026-09-15, источник — Indeed.