Job description

Role Summary:

The Junior AI/ML Engineer contributes to the design, build, and delivery of end-to-end AI/ML solutions under the guidance of senior engineers. This role is engineering-first, applying data science and machine learning as tools within well-engineered software systems.

Engineers at this level focus on well-defined implementation tasks within a larger solution, learning the full lifecycle - design, development, validation, and production handoff - through pairing, code review, and structured mentoring.

AI & ML Development:

Implement ML models and components against established designs, using structured, time-series, and unstructured data
Run and document model validation, evaluation, and error analysis under senior guidance
Build familiarity with the team's AI/ML techniques and how they are applied to engineering, quality, and product use cases

Software & Systems Engineering:

Contribute production-quality code to AI systems, including:
Data pipelines and feature engineering
Model training and inference services
Components of agentic solutions combining LLM and other systems
Write clean, maintainable, and testable code (primarily Python), responding constructively to code review
Use the team's shared AI/ML components and engineering frameworks

Delivery & Execution:

Deliver well-scoped implementation tasks reliably, escalating blockers early
Participate in requirement clarification and solution iteration with the team
Support preparation of solutions for operationalization in partnership with MLOps teams

Growth Expectations:

Progress toward independent ownership of implementation tasks end-to-end
Develop breadth across data, modeling, and software concerns
Actively seek and apply feedback from senior engineers

Basic Qualifications:

Bachelor's degree in engineering, computer science, applied mathematics, or a related field
A minimum of 1 year of experience
Solid software engineering fundamentals
Exposure to machine learning through coursework, internships, or projects
Proficiency in Python; familiarity with common ML libraries
Willingness to work across data, modeling, and software concerns

Preferred Qualifications:

Internship or project experience deploying ML in real systems
Exposure to cloud-based data or ML platforms
Interest in LLM-based and agentic solutions
Familiarity with software delivery practices (version control, CI, testing)