Staff Research Engineer: Frontier AI & RL Benchmarks

turing; USA; Remote; USD 250.000 - 400.000; Vollzeit

Benefits dieser Stelle

Equity

Conference publication opportunities

High autonomy

Zusammenfassung

Turing is seeking a staff-level researcher to lead research engineering on frontier AI systems, shaping datasets, reinforcement learning environments, and benchmarks. You will own technical direction and translate findings into production-grade improvements with autonomy and impact.

Responsibilities include guiding investigations across domains, designing rigorous experiments, and contributing to the research community through publications and open-source work.

Qualifikationen

• Substantial research background in machine learning, AI systems, or related fields; demonstrated technical leadership.
• Deep proficiency with modern AI and ML tools for training, testing, and evaluating models at scale.
• Track record of designing experiments that yield evidence-based, reproducible conclusions.
• Strong communication skills for researchers and cross-functional partners.
• History of contributing to AI research through publications, open-source work, or industry equivalents.

Aufgaben

• Lead investigations into capabilities and training methods of frontier AI systems across domains.
• Design rigorous experiments, prototypes, tooling, and evaluation frameworks for synthetic data and RL.
• Build and operate RL environments for coding and browser-use agents and function-calling workflows.
• Translate research findings into scalable product and platform improvements with cross-functional teams.
• Contribute to the research community via publications, open-source work, workshops, and mentoring.
• Uphold practices for experimental rigor, data quality, reproducibility, and interpretation.

Kenntnisse

Substantial research background in ML/

Deep proficiency with AI/ML tools

Experimental design & reproducible 연구

Jobbeschreibung

Turing is seeking a staff-level researcher to lead research engineering on frontier AI systems, shaping datasets, reinforcement learning environments, and benchmarks. You will own technical direction and translate findings into production-grade improvements with autonomy and impact.

Responsibilities include guiding investigations across domains, designing rigorous experiments, and contributing to the research community through publications and open-source work.