Associate Engineer, Analytical AI Engineering

About the Role

The Associate Engineer is a developing individual contributor who delivers reliable, well-scoped engineering work within established patterns. You will help build data pipelines, ML workflow components, and platform features that support production-ready AI/ML solutions. This role is well suited for early-career engineers who are ready to take on real ownership while building toward increasingly independent delivery. The ideal candidate is dependable, curious, and eager to grow.

Key Responsibilities

Technical Delivery

• Implement data pipelines, ML workflow components, and platform features following established architecture patterns and coding standards.
• Write readable, maintainable, testable code with limited guidance after initial design alignment with senior engineers.
• Deliver well-scoped work reliably and on schedule; understand how your work fits into the larger solution.

Problem Solving

• Write and maintain tests for your work; ensure changes are tested before deployment.
• Troubleshoot issues within your assigned pipelines and features with minimal guidance; identify root causes and propose solutions.
• Navigate the codebase and data designs with growing independence after initial orientation.

Collaboration & Growth

• Contribute input to team scoping and design exercises; share observations that improve how the team approaches recurring problems.
• Explain your work clearly to teammates, including what you built, why, and any trade-offs.
• Demonstrate awareness of the business context for your work and how it connects to the team's broader goals.
• Take ownership of your development; actively seek feedback and apply it to strengthen your technical and professional skills.

Requirements & Tech Stack

Education

• BA/BS required (quantitative or engineering discipline preferred).

Experience

• 0-2 years of experience in data engineering, software engineering, ML engineering, or a related field; relevant advanced degrees contribute to required years of experience.

Technical Skills

• Proficiency in Python and SQL; familiarity with data pipeline development and common processing patterns.
• Working knowledge of version control (Git), testing practices, code review, and documentation.
• Exposure to cloud environments (AWS, Azure, or Databricks); willingness to develop deeper platform proficiency.
• Familiarity with ML concepts and workflows (model training, feature engineering, data preparation); MLOps experience a plus.

Competencies

• Works effectively within team guidelines and standards.
• Builds positive working relationships with teammates and cross-functional partners.
• Reliable delivers commitments and communicates proactively when blockers arise.
• Demonstrates curiosity and commitment to growing technical and professional skills.