AI/ML Engineer

Air InfoSecAustin, TX
Onsite

About The Position

The AI/ML Engineer (Intern Level 2) will support the Texas Department of Transportation (TxDOT) on the ITD AI Development team's rapid development initiatives using AI/ML tools and platforms. This role focuses on driving business innovation at TxDOT through the evaluation and application of emerging AI/ML technologies. The individual will contribute to the design, development, and deployment of AI/ML models and applications tailored to specific business use cases. This position collaborates closely with data, engineering, and software development teams to bring AI-driven solutions from concept to implementation.

Requirements

  • 2 years of experience with Python.
  • 2 years of experience with SQL.
  • 2 years of experience with data visualization tools such as Power BI, Tableau, Streamlit, R Shiny, or Matplotlib.
  • 2 years of experience with object-oriented programming and design patterns.
  • 2 years of experience with unit testing, CI/CD, Git, and containerization (Docker).
  • 2 years of experience with data pipelines and ETL tools such as Airflow, Prefect, or cloud-native equivalents.
  • 2 years of experience with model deployment (REST APIs, gRPC, serverless), monitoring, and versioning.
  • 2 years of experience with AWS, Azure, GCP, or OCI AI services.
  • 2 years of experience with cloud-native training/inference environments such as SageMaker, Bedrock, Vertex AI, or Azure ML.
  • 2 years of experience with Kubernetes and Docker.
  • 2 years of experience with code assist tools such as Claude Code, Codex, or Cursor.

Nice To Haves

  • 2 years of experience or academic coursework related to transportation and traffic analysis.
  • Local candidates only; must currently reside within 50 miles of the Austin, Texas work location.
  • Candidates must be authorized to work in the U.S.

Responsibilities

  • Evaluate emerging AI trends, tools, and vendor solutions against business use cases.
  • Run proof-of-concepts (PoCs) to test the feasibility of new ideas.
  • Design and build applications and AI/ML models tailored to specific use cases, including predictive analytics, natural language processing, and computer vision, prioritized for the AI Program.
  • Create scalable AI pipelines that can be integrated into existing systems.
  • Collaborate with data, engineering, and software development teams.
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