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Posted on 2026/10/07

Artificial Intelligence/Machine Learning Engineer 2 - Intern - Location - Austin TX

Conquest Consulting

Austin, TX, United States

Contractor

Job Title: Artificial Intelligence/Machine Learning Engineer 2 - Intern Service Term Expected: 12-month duration Location: Austin, TX 78744

This role requires onsite presence 4–5 days per week.

Minimum Yrs of Experience, Skills, and Qualifications

  • 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

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
  • Exposure to data analysis, data migration, and basic model development
  • Understanding of basic software development and testing concepts

Preferred (Exposure or Academic Experience is Acceptable)

  • 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

Key Attributes for Success

  • Strong analytical and problem-solving skills
  • Ability to communicate technical concepts clearly to non-technical audiences
  • Willingness to learn and adapt in a fast-evolving technical environment
  • Attention to detail and commitment to data quality
  • Collaborative mindset and openness to mentorship and feedback