Research Engineer, Post-Training

Collision; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Collision AI in San Francisco is looking for a researcher to develop training methods and infrastructure for frontier cybersecurity models, focusing on post-training and continual learning from real security work.

You’ll own the full experimental cycle—from hypothesis to deployed models—identifying signals in production telemetry, building datasets, testing algorithms, and evaluating model performance, while collaborating with founders to shape the product and research direction.

Qualifications

• Experience training large language models.
• Proficiency in PyTorch, JAX, or a comparable ML framework, with the engineering skills to turn research ideas into working systems.
• A master’s degree or relevant research experience.

Responsibilities

• Develop training methods and infrastructure behind frontier cybersecurity models.
• Own the full experimental cycle—from hypothesis to deployed models.
• Collaborate with founders to shape the product direction and research roadmap.

Skills

LLM training

Experimental judgment

Distributed training

Open-source contributions

Independent thinking

Education

Master's degree or relevant research experience

Tools

PyTorch

JAX

Job description

Collision AI is building frontier cybersecurity models to help defend our customers. We’re looking for a researcher to develop the training methods and infrastructure behind them, with a focus on post-training and continual learning from real security work.

You’ll take research ideas from an initial hypothesis to deployed models. That means identifying useful signals in production telemetry, building training datasets, testing new algorithms, and developing evaluations that measure how well our models and agents perform. You’ll own the full experimental cycle, combining research with hands-on LLM training and serving.

As an early member of the team, you’ll work directly with the founders and design partners to decide what we build and how. Your work will shape the technical foundations, product direction, and the way we conduct research as a company.

Required qualifications

• Experience training large language models.
• Proficiency in PyTorch, JAX, or a comparable ML framework, with the engineering skills to turn research ideas into working systems.
• Strong experimental judgment: forming testable hypotheses, choosing meaningful measurements, and using results to guide the next experiment.
• Experience with distributed training, high-performance computing, or debugging experiments across large compute clusters.
• Contributions to open-source ML research, training systems, or evaluation infrastructure.
• Evidence of independent technical thinking through research, open-source work, or ambitious personal projects.
• A master’s degree or relevant research experience.