MTS: Frontier AI Simulation Architect

Collinear AI, Inc.; San Francisco (CA); Hybrid; USD 180.000 - 260.000; Vollzeit

Zusammenfassung

Collinear AI, Inc. in San Francisco seeks a Member of Technical Staff (Research) to bridge frontier research and production engineering. You will design ultra-realistic simulation environments, develop evaluation stacks, and push state-of-the-art in AI reliability across the ML stack.

You will collaborate with founders and research staff to shape the roadmap, translate novel RL approaches into scalable infrastructure, and contribute to high-impact open-source benchmarks.

Qualifikationen

• A Bachelor’s, Master’s, or PhD in a technical field (CS, Math, Physics, etc.), or demonstrated proof of work through open-source contributions or industry experience.
• Strong software engineering fundamentals with the ability to build robust, scalable infrastructure in a Python-friendly, CLI-first environment.
• Principled understanding of foundation models, how they are constructed, evaluated, and optimized.
• Experience conducting research or technical experiments with a focus on reproducibility and data-driven results.

Aufgaben

• Build Agentic Environments: design and implement ultra-realistic, long-horizon simulation environments for agents.
• Programmatic Verification: develop judges and evaluations that measure genuine capability and safety beyond benchmarks.
• Close the Loop: design and execute post-training runs to deliver frontier performance on open-source models.
• Rapid Iteration: debug and iterate across the ML stack, keeping tools CLI-first and developer-friendly.
• Collaborate: work daily with founders and researchers to shape the roadmap and push AI reliability.

Kenntnisse

Software engineering

Python CLI

Machine learning

Research experience

Reproducibility

Ausbildung

CS/Math/Physics degree

Tools

RL frameworks

Open-source projects

Jobbeschreibung

Collinear AI, Inc. in San Francisco seeks a Member of Technical Staff (Research) to bridge frontier research and production engineering. You will design ultra-realistic simulation environments, develop evaluation stacks, and push state-of-the-art in AI reliability across the ML stack.

You will collaborate with founders and research staff to shape the roadmap, translate novel RL approaches into scalable infrastructure, and contribute to high-impact open-source benchmarks.