Staff Research Engineer, Enterprise Knowledge

turing; United States; Remote; USD 250,000 - 400,000; Full time

Job summary

Turing is seeking a research-focused engineer to operate at the intersection of research and engineering. You will build large-scale datasets and RL environments powering post-training for leading AI labs and enterprises, tackling multi-step workflows in finance, sales, retail, and more.

You will design rigorous experiments, develop research-grade tooling, and evaluate models with modern AI methods, translating insights into product improvements in collaboration with multiple teams.

Qualifications

• Strong research background with experience formulating and executing original research in machine learning, AI, or a closely related technical field.
• Solid engineering skills to build research-grade prototypes, tooling, and evaluation frameworks.
• Deep understanding of modern large language models, reinforcement learning, post-training techniques, and the frontier AI research landscape.
• Excellent experimental design, quantitative analysis, and cross-functional communication skills.

Responsibilities

• Investigate the capabilities, limitations, and training methods of frontier AI systems and formulate research questions that shape product and platform strategy.
• Design and run rigorous experiments, building research-grade datasets, prototypes, tooling, and evaluation frameworks.
• Train, test, and evaluate models using modern AI and machine learning tools, and draw clear, evidence-based conclusions from results.
• Translate research findings into improvements for products, platforms, and AI capabilities by collaborating with Research, Engineering, Product, and Operations teams.
• Build environments for software engineering and coding agents, UI environments for computer-use and browser-use agents, and MCP-based environments for general function-calling agents.
• Share findings through technical reports, publications, open-source work, workshops, or conference participation.

Skills

Research background

Engineering skills

LLMs & RL knowledge

Experimental design

Job description

Role overview

This position sits at the intersection of research and engineering, building large-scale datasets and reinforcement learning environments that power post-training for leading AI labs and enterprises. The environments evaluate and improve models on complex, multi-step workflows in high-value domains such as finance, sales, retail, developer tools, collaboration, and customer experience. Researchers investigate high-impact questions on synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

Responsibilities

• Investigate the capabilities, limitations, and training methods of frontier AI systems and formulate research questions that shape product and platform strategy.
• Design and run rigorous experiments, building research-grade datasets, prototypes, tooling, and evaluation frameworks.
• Train, test, and evaluate models using modern AI and machine learning tools, and draw clear, evidence-based conclusions from results.
• Translate research findings into improvements for products, platforms, and AI capabilities by collaborating with Research, Engineering, Product, and Operations teams.
• Build environments for software engineering and coding agents, UI environments for computer-use and browser-use agents, and MCP-based environments for general function-calling agents.
• Share findings through technical reports, publications, open-source work, workshops, or conference participation.

Requirements

• Strong research background with experience formulating and executing original research in machine learning, AI, or a closely related technical field.
• Solid engineering skills to build research-grade prototypes, tooling, and evaluation frameworks.
• Deep understanding of modern large language models, reinforcement learning, post-training techniques, and the frontier AI research landscape.
• Excellent experimental design, quantitative analysis, and cross-functional communication skills.

Benefits and work setup

• Compensation range of $250,000 to $400,000 OTE plus equity.
• Opportunity to publish at leading conferences such as ICLR, ICML, and NeurIPS.
• High autonomy, rapid iteration, and direct collaboration with leading AI labs and enterprises on high-value post-training and RL environment design.