# MTS - Research Scientist Internship at Collinear AI

MTS - Research Scientist Internship at Collinear AI in Sunnyvale, California and 2 more. On-site, full-time. Posted September 21, 2026.

- Company: Collinear AI
- Location: Sunnyvale, California and 2 more
- Workplace: On-site
- Job type: Full-time
- Posted: 2026-09-21
- Apply: https://jobs.ashbyhq.com/collinear-ai/ae85fd08-dfd8-42e5-9b3b-9921ba24742b/application
- Source: https://jobmagic.ai/jobs/mts-research-scientist-internship-collinear-ai-1sb83z

## Requirements

- Technical Foundation: 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.
- Engineering Rigor: A strong foundation in software engineering with the ability to build robust, scalable infrastructure. You should be comfortable in a Python-friendly, CLI-first development environment.
- ML Fluency: A principled understanding of foundation models, including how they are constructed, evaluated, and optimized.
- Empirical Mindset: Experience conducting research or technical experiments with a focus on reproducibility and data-driven results.

## Description

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:**

- **Build Agentic Environments**: Design and implement the next generation of "SimLabs", ultra-realistic, long-horizon simulation environments where agents learn to navigate ambiguity and maintain context.

- **Programmatic and Agentic Verification**: Develop rigorous, policy-aware judges and evaluations that measure genuine capability and safety beyond simple benchmarks.

- **Close the Loop**: Design and execute high-quality post-training runs (CPT, SFT, RL) to deliver frontier performance on open-source models using curated, high-signal data.

- **Collaborate**: Work daily with the founders and research staff to shape the roadmap and push the state-of-the-art in AI reliability.

- **Create**. Work on analyzing model failure modes and creating frontier data pipelines which scale with test-time compute.

### **About You**

We are looking for individuals who demonstrate a rare combination of technical depth, research intuition, and high agency.

- **Technical Foundation:** 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.

- **Engineering Rigor:** A strong foundation in software engineering with the ability to build robust, scalable infrastructure. You should be comfortable in a Python-friendly, CLI-first development environment.

- **ML Fluency:** A principled understanding of foundation models, including how they are constructed, evaluated, and optimized.

- **Empirical Mindset:** Experience conducting research or technical experiments with a focus on reproducibility and data-driven results.

### **What will make you stand out**

- **Research Taste:** You have a strong intuition for identifying what matters in complex problem spaces. You can balance deep research exploration with the pragmatism needed to ship a product.

- **Impact-Driven Agency:** You care about outcomes, not just activity. You don't wait for a ticket; you identify gaps in the system, build the solution, and ensure it moves real-world metrics for frontier AI labs.

- **Domain Expertise:** Prior experience with Reinforcement Learning (RLHF/RLAIF), simulation systems, or building long-horizon agentic environments.

- **Proven Track Record:** A history of contributing to influential ML research (e.g., publications at NeurIPS, ICLR, ICML) or maintaining high-impact open-source projects.

- **Post-Training Experience:** Experience fine-tuning or evaluating large-scale models to deliver "frontier performance" on open-source benchmarks.

 

### **Why Join Collinear**

- **Own the Frontier:** Work on the most pressing problem in AI today: making agents reliable enough for production.

- **High Density of Talent:** Join a small, elite team where you will be pushed to do your life's work.

- **Elite Compensation:** We offer competitive salary and equity packages to ensure we attract the best of the best.

- **Direct Impact:** At a seed-backed startup, your work directly shapes the company's trajectory and the future of AI safety.