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About the Role
Collinear's Internship program is designed for PhD students who are eligible to do a 12-week internship. Start dates are flexible and can be extended. As an MTS - Research Scientist (Applied Scientist), you will help build the data engine for frontier AI. You will develop the high-fidelity environments and evaluation stacks that the world’s leading AI labs rely on to stress-test their most advanced agents. You will work across domains including Computer Use, Enterprise MCP/Toolcalling and Coding. Verifier Design, Simulated Personas, Benchmarking Personal AGI are some of the research areas we work on.
Responsibilities
- Design and implement the next generation of "SimLabs", ultra-realistic, long-horizon simulation environments where agents learn to navigate ambiguity and maintain context.
- Develop rigorous, policy-aware judges and evaluations that measure genuine capability and safety beyond simple benchmarks.
- Design and execute high-quality post-training runs (CPT, SFT, RL) to deliver frontier performance on open-source models using curated, high-signal data.
- Work daily with the founders and research staff to shape the roadmap and push the state-of-the-art in AI reliability.
- Analyze model failure modes and create frontier data pipelines that scale with test-time compute.
Requirements
- A Bachelor’s, Master’s, or PhD in a technical field (CS, Math, Physics, etc.), or a demonstrated "proof of work" through significant open-source contributions or industry experience.
- Strong foundation in software engineering with the ability to build robust, scalable infrastructure.
- Comfortable in a Python-friendly, CLI-first development environment.
- Principled understanding of foundation models, including how they are constructed, evaluated, and optimized.
- Experience conducting research or technical experiments with a focus on reproducibility and data-driven results.
Skills
- Python
- Reinforcement Learning (RLHF/RLAIF)
- Simulation systems
- Building long-horizon agentic environments
- Fine-tuning large-scale models
- Evaluating large-scale models
Location
- Remote
Work Type
- Internship
- Full-time
Experience Level
- PhD student
- Intern
Education Level
- PhD
- Master's
- Bachelor's
Salary/Compensations
- Competitive salary and equity packages
Benefits
- Flexible start dates
- Potential for internship extension
- Work on the most pressing problem in AI today: making agents reliable enough for production.
- High density of talent
- Elite compensation
- Competitive salary and equity packages
- Direct impact on company trajectory and the future of AI safety
About the Company
- Collinear is working on the most pressing problem in AI today: making agents reliable enough for production.
- We are a seed-backed startup.