Onsite Artificial Intelligence/Machine Learning Engineer 2 - Intern (Austin TX)

Qualifications

Minimum Yrs Of Experience, Skills, And Qualifications

Level & Experience Alignment

Typically 1 3 years of academic, internship, or entry level experience in AI, data science, software engineering, or a related field

14 more items(s)

Responsibilities

The AI Apprenticeship Program establishes a sustainable and governed pathway for developing entry level AI talent in support of AI Strategic Plan

Under supervision, the intern will:

Assist in evaluating emerging AI trends, tools, and vendor solutions against defined business use cases

7 more items(s)

More job highlights

Job description

Dice is the leading career destination for tech experts at every stage of their careers. Our client, TexcelVision Inc., is seeking the following.

Apply via Dice today!

The workers responsibilities and skills must include:

The AI Apprenticeship Program establishes a sustainable and governed pathway for developing entry level AI talent in support of AI Strategic Plan.

Under supervision, the intern will:

Assist in evaluating emerging AI trends, tools, and vendor solutions against defined business use cases

Support proof of concept (PoC) efforts to assess feasibility, data readiness, and potential value

Contribute to the development of AI/ML models and prototype applications for prioritized use cases

Help design and document data and AI pipelines that integrate with existing systems

Create reports, analyses, and presentations that communicate findings and outcomes clearly

Collaborate with data, engineering, software development, and governance teams

Minimum Yrs Of Experience, Skills, And Qualifications

Level & Experience Alignment

Level 2 (Intern / Apprentice Equivalent):

Typically 1 3 years of academic, internship, or entry level experience in AI, data science, software engineering, or a related field

Possesses foundational knowledge of common concepts, tools, and practices

Works under guidance using established processes and standards

Does not typically exercise independent production decision making

Minimum Qualifications, Skills, And Experience

Education / Learning Background

• Coursework toward or completion of a degree in Computer Science, Data Science, Engineering, Mathematics, or related discipline

• Demonstrated interest in artificial intelligence, machine learning, and applied analytics

Technical Skills (Foundational / Developing)

Proficiency in Python

Familiarity with object oriented programming concepts

Experience with version control (Git)

Exposure to data processing, analysis, and basic model development

Understanding of basic software development and testing concepts

Preferred Skills And Qualifications

Familiarity with one or more of the following (hands on or academic):

• Data pipelines (e.g., Airflow, Prefect, or cloud native equivalents)

• Model deployment concepts (e.g., REST APIs, serverless patterns)

• Cloud platforms or AI services (AWS, Azure, Google Cloud Platform, OCI)

• Containerization concepts (Docker)

• CI/CD fundamentals

• Monitoring or model versioning concepts