AI Research Engineer

Role Overview

Colleague AI is hiring an AI Research Engineer to help advance the next generation of AI systems for K–12 education. This position will be in-person only, located in Kirkland, WA.

This role is ideal for an engineer who combines strong technical depth with curiosity, fast learning, and an open-minded approach to applied research. You will work on cutting-edge problems at the intersection of large language models (LLMs), AI agents, learning environments, evaluation, human-AI collaboration, and education technology.

A key goal of this role is to build high-quality AI applications that bring frontier AI-agent ideas into real-world K–12 settings. Examples of relevant research and product directions include agent learning from classroom environments, long-horizon educational workflows, AI tutoring and grading agents, benchmark design, feedback-driven improvement, multi-agent teacher/student simulations, and rigorous evaluation of AI systems in authentic educational use cases.

Responsibilities

• Apply frontier AI-agent methods to K–12 teaching and learning workflows.
• Lead applied research on LLMs, AI agents, evaluation systems, and educational AI.
• Design rigorous evaluation frameworks for AI tutoring, grading, lesson generation, classroom agents, and other educational use cases.
• Design experiments to measure model behavior, diagnose failures, compare approaches, and improve system performance.
• Build benchmarks and datasets that measure long-horizon agent behavior, feedback-driven learning, reliability, safety, and instructional quality.
• Collaborate with engineering and product teams to turn prototypes into production-ready features.
• Stay current with advances in LLMs, agentic AI, retrieval-augmented generation, evaluation methods, synthetic data, and AI safety.
• Publish research papers, technical reports, benchmarks, datasets, or open-source tools that establish Colleague AI as a thought leader in AI for education.

Qualifications

• Master’s, or Ph.D. or equivalent advanced education in Computer Science, Machine Learning, Artificial Intelligence, Natural Language Processing, Data Science, Learning Sciences, Educational Technology, or a related technical field.
• 3+ years of working experience in the relevant field. 
• Strong programming/engineering skills in Python and ML frameworks such as PyTorch, TensorFlow, JAX, LangChain/LangGraph or similar.
• Strong research and engineering background in machine learning, deep learning, NLP, large language models, AI agents, or human-AI interaction.
• Experience optimizing model performance in production or production-like environments.
• Strong understanding of model validation, statistical analysis, error analysis, and empirical research methods.
• Strong collaboration skills and interest in working with engineers, researchers, product teams, educators, and school partners.

Preferred Qualifications

• Experience with LLM agents, tool-using agents, multi-agent systems, autonomous workflows, or long-horizon agent evaluation.
• Experience with educational AI, intelligent tutoring systems, automated feedback, grading, curriculum generation, or classroom technology.
• Experience evaluating AI systems for safety, reliability, fairness, privacy, or age-appropriate behavior.

Compensation

Base salary: $120K-$200K

Colleague AI offers competitive compensation, including base salary, equity, and benefits. Final compensation will be determined based on experience, qualifications, location, and role scope.

How to Apply

Please submit the following materials:

• A brief statement of interest describing your relevant research interests, technical experience, and motivation for joining Colleague AI.
• Evidence of qualifications, such as a portfolio of prior work, selected publications, GitHub repositories, technical writing, demos, or deployed systems.
• A current CV.

Applications should apply via this link.

Deadline

We will start to review applications after 8/31/2026. The position will remain open until it is filled. The starting date will be immediately after the position is filled.