Research Scientist - Internship

Collinear is an early-stage, seed-backed startup helping enterprises deploy AI they can trust.

Our platform simulates realistic, multi-turn user journeys to stress-test agents. It analyzes behavior with policy-aware judges across 20+ performance, safety, and reliability metrics. It then curates high-signal, semi-synthetic data for post-training (CPT/SFT/RL).

The closed loop—simulate → analyze → improve—turns evaluation gaps into measurable quality lift in production.Why Join Collinear

• Own meaningful surface area: design and ship features across simulations, judges, and post-training data pipelines.

• See impact quickly: small team, short iteration cycles, production users.

• Work at the core of LLM quality: multi-turn agent sims, metric/benchmark design, CPT/SFT/RL data curation.

• Direct access to decision-makers: collaborate daily with founders on roadmap and results.

• Solid footing for speed: seed-backed, active customer pilots, and room to shape the direction.

Join us in pushing the boundaries of what's possible in AI! Learn more about the company here.

About the Role
As a Research Scientist Intern, you will support our technical team in developing and improving our core product pipeline. This internship offers a unique opportunity to contribute to cutting-edge research in AI safety and reliability while gaining valuable industry experience. You'll work alongside experienced researchers and engineers to help translate research into practical applications.

Key Responsibilities

• Assist in implementing and testing machine learning models and systems

• Write blogposts

• Open source datasets and models

• Write research papers at top conferences (COLM, ICLR, NeurIPS)

• Support research activities related to foundation models and AI safety

• Help optimize ML performance and contribute to distributed training efforts

• Participate in data curation and analysis for model improvement

• Collaborate with the technical team on research projects

About You

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field

• Strong foundation in machine learning concepts and techniques

• Experience with PyTorch, TensorFlow, or similar ML frameworks

• Solid programming skills, particularly in Python

• Basic understanding of foundation models and their applications

• Eagerness to learn about AI safety and reliability

• Strong problem-solving abilities and attention to detail

• Excellent communication skills and ability to work in a team environment

What We Offer

• Hands-on experience with cutting-edge AI research and development

• Mentorship from industry experts

• Exposure to real-world applications of foundation models

• Collaborative and innovative work environment

• Opportunity to contribute to projects with significant impact

Duration

3-6 months, with potential for extension or conversion to full-time based on performance

This will be a paid position in line with market competitive rates!