Junior AI/ML Engineer (Need local candidates only)

Below is the job description for the position:

Job Title: Junior AI/ML Engineer

Location: Austin, TX 78744 (Fully Onsite)

Duration: 12+ Months (Possible Extension)

Position Summary

The AI Apprenticeship Program is designed to create a sustainable and well-governed pipeline for developing entry-level AI talent in support of the Texas Department of Transportation (TxDOT) AI Strategic Plan.

Under general supervision, the Junior AI/ML Engineer (Intern/Apprentice) will assist in researching emerging artificial intelligence technologies, supporting proof-of-concept initiatives, and contributing to the development of machine learning models and prototype applications. This role offers an excellent opportunity for early-career professionals to gain hands-on experience working with AI, data engineering, and software development teams.

Key Responsibilities • 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 business value. • Contribute to the development and testing of AI/ML models and prototype applications. • Help design, document, and maintain data and AI pipelines that integrate with existing enterprise systems. • Prepare reports, analyses, and presentations to clearly communicate findings and recommendations. • Collaborate with data engineers, software developers, AI specialists, and governance teams. • Participate in code reviews, testing, and documentation activities. • Follow established development standards, processes, and best practices.

Experience Level and Role Alignment

Level 2 – Intern / Apprentice Equivalent • Typically 1–3 years of academic, internship, or entry-level experience in artificial intelligence, data science, software engineering, or a related field. • Possesses foundational knowledge of industry concepts, tools, and methodologies. • Works under supervision and follows established processes and standards. • Does not typically make independent production decisions.

Minimum Qualifications

Education • Coursework toward, or completion of, a Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline. • Demonstrated interest in artificial intelligence, machine learning, and applied analytics.

Technical Skills • Proficiency in Python programming. • Understanding of object-oriented programming (OOP) principles. • Experience with version control tools such as Git. • Exposure to data processing, analysis, and basic machine learning model development. • Knowledge of software development lifecycle (SDLC) and testing fundamentals.

Preferred Skills and Qualifications • Familiarity with one or more of the following through academic projects, internships, or hands-on experience: • Data pipeline tools such as Airflow, Prefect, or cloud-native equivalents. • Model deployment concepts, including REST APIs and serverless architectures. • Cloud platforms and AI services such as AWS, Azure, Google Cloud Platform (GCP), or Oracle Cloud Infrastructure (OCI). • Containerization technologies such as Docker. • CI/CD fundamentals. • Monitoring, experiment tracking, or model versioning concepts.

Ideal Candidate Profile

The ideal candidate is a motivated early-career professional or recent graduate with a strong interest in artificial intelligence and machine learning. They should possess solid programming skills in Python, an eagerness to learn emerging technologies, and the ability to collaborate effectively in a team-oriented environment.

Thanks & Regards

Infojini Consulting

Website: https://www.infojiniconsulting.com

Address: 10015 Old Columbia Road, Suite B 215, Columbia, MD 21046