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Artificial Intelligence/Machine Learning Engineer 2 for Austin, TX, onsite job (needs local to Austin)
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.
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
Artificial Intelligence/Machine Learning Engineer 2 for Austin, TX, onsite job (needs local to Austin)
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.
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