AI/ML Engineer

Overview:

• Artificial Intelligence/Machine Learning Engineer 2 will support TxDOT s AI Development team in building and evaluating AI/ML solutions that drive business innovation.
• The role involves AI/ML application development, proof-of-concepts, data pipelines, model deployment, visualization, and cloud-based AI services.

Responsibilities:

• Evaluate emerging AI/ML technologies, tools, platforms, and vendor solutions against business use cases.
• Develop proof-of-concepts (PoCs) to validate AI/ML solutions and new ideas.
• Design and build AI/ML applications and models for use cases such as predictive analytics, NLP, and computer vision.
• Develop scalable AI/ML pipelines and integrate them with existing systems.
• Build data pipelines and ETL workflows using Airflow, Prefect, or cloud-native alternatives.
• Support model deployment, monitoring, versioning, and inference through REST APIs, gRPC, serverless platforms, or similar approaches.
• Collaborate with data, software engineering, and development teams.
• Use modern development practices including Git, CI/CD, Docker, unit testing, and object-oriented programming.
• Leverage cloud AI/ML services across AWS, Azure, Google Cloud Platform, or OCI.

Required Qualifications:

• 2 3 years of experience in AI/ML engineering, software development, data engineering, or a closely related area.
• Strong working knowledge of Python and SQL.
• Experience with data visualization tools such as Power BI, Tableau, Streamlit, R Shiny, or Matplotlib.
• Knowledge of object-oriented programming and design patterns.
• Understanding of unit testing, CI/CD, Git, and Docker/containerization.
• Familiarity with data pipelines and ETL, including Airflow, Prefect, or cloud-native equivalents.
• Knowledge of AI/ML model deployment, monitoring, and versioning.
• Exposure to REST APIs, gRPC, serverless architectures, or similar deployment methods.
• Familiarity with at least one major cloud platform: AWS, Azure, Google Cloud Platform, or OCI.
• Exposure to cloud-native AI/ML platforms such as SageMaker, Bedrock, Vertex AI, or Azure ML.
• Knowledge of Kubernetes and Docker.
• Familiarity with modern AI coding assistants, such as Claude Code, Codex, Cursor, or similar tools.