Need - Artificial Intelligence/Machine Learning Engineer 2- Austin, TX, Onsite - Locals Only

Austin, TX, US • Posted 2 days ago • Updated 5 hours ago
Contract W2
Contract Independent
Contract Corp To Corp
No Travel Required
On-site
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Amazon SageMaker
  • Artificial Intelligence
  • C++
  • Cloud Computing
  • Collaboration
  • Computer Vision
  • Continuous Delivery
  • Continuous Integration
  • Data Engineering
  • Docker
  • Git
  • Good Clinical Practice
  • Google Cloud Platform
  • Innovation
  • Java
  • Kubernetes
  • Machine Learning (ML)
  • Microsoft Azure
  • Natural Language Processing
  • OCI
  • Predictive Analytics
  • Python
  • Software Development
  • Testing
  • Training
  • Use Cases
  • Vertex

Summary

Hi,

Hope you're doing well!

Title: Artificial Intelligence/Machine Learning Engineer 2

Work Location: Austin, TX, onsite job

Client: State of Texas
Department: Texas Department of Transportation (TXDOT)
Exp:13+

Job Description

The AI Innovation team in ITD undertakes rapid development initiatives using AI/ML tools and platforms with the goal to drive business innovation at the Texas Department of Transportation.

Evaluate emerging AI trends, tools, and vendor solutions against business use-cases.

Run proof-of-concepts (PoCs) to test feasibility of new ideas.

Design and build applications and AI/ML models tailored to specific use cases (e.g., predictive analytics, natural language processing, 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.

Minimum Yrs of Experience, Skills, and Qualifications

Possesses raw knowledge and skillset through coursework with some hands on

work experience in the following areas:

Strong Python, familiarity with Java / C++ / Go for production environments

Object-oriented programming & design patterns

Unit testing, CI/CD, Git, containerization (Docker)

Data pipelines (Airflow, Prefect, or cloud-native equivalents)

Model deployment (REST APIs, gRPC, serverless), monitoring, and versioning

AWS / Azure / Google Cloud Platform / OCI AI services

Cloud-native training/inference environments (SageMaker, Vertex AI, Azure ML)

Kubernetes for scalable inference

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10123013
  • Position Id: 8941663
  • Posted 2 days ago
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