Senior Research Engineer, Frontier Data

turing; United States; Remote; USD 250,000 - 350,000; Full time

Job summary

Turing is seeking a Senior Research Engineer to advance frontier AI systems through large-scale datasets, RL environments, and evaluation frameworks that guide post-training improvements for coding, UI, and function-calling agents. This role sits at the intersection of research and engineering, turning experimental insights into scalable production capabilities.

You will collaborate with research, engineering, product, and operations teams, produce rigorous evaluations, and contribute to

Qualifications

• Strong ML research background with experimental design.
• Hands-on experience training, testing, and evaluating models.
• Ability to translate research findings into product, platform, or capability improvements.
• Commitment to reproducibility, data quality, and sound interpretation of results.
• Comfort collaborating across research, engineering, product, and operations.

Responsibilities

• Formulate and investigate research questions about frontier model capabilities, limitations, and training methods.
• Design and run rigorous experiments, drawing evidence-based conclusions and iterating from hypothesis to insight.
• Build research-grade datasets, prototypes, tooling, and evaluation frameworks for coding, UI, and function-calling environments.
• Partner with research, engineering, product, and operations to move ideas into scalable production systems.
• Contribute to the broader research community through reports, publications, or open-source work.

Skills

Frontier AI

Experimental design

Statistical analysis

Research translation

Team collaboration

Tools

RL environments

Synthetic data generation

Evaluation frameworks

Prototyping tooling

Job description

Role overview

A senior research engineering position focused on advancing frontier AI systems through large-scale datasets, reinforcement learning (RL) environments, and evaluation frameworks used to post-train leading models. The role sits at the intersection of applied research and engineering, translating experimental findings into scalable improvements for software-engineering agents, computer-use or browser-use agents, and MCP-based function-calling systems. Work spans synthetic and agentic data generation, model understanding, benchmark design, and rigorous experimentation across high-value domains.

Responsibilities

• Formulate and investigate research questions about frontier model capabilities, limitations, and training methods
• Design and run rigorous experiments, drawing evidence-based conclusions and iterating quickly from hypothesis to validated insight
• Build research-grade datasets, prototypes, tooling, and evaluation frameworks for coding, UI, and function-calling environments
• Partner with research, engineering, product, and operations teams to move promising ideas into scalable production systems
• Contribute to the broader research community through technical reports, publications, open-source work, or conference participation where appropriate

Requirements

• Strong background in machine learning research, including experimental design and statistical analysis
• Hands-on experience training, testing, and evaluating models using modern AI tooling
• Ability to translate research findings into product, platform, or capability improvements
• Commitment to reproducibility, data quality, and sound interpretation of experimental results
• Comfort collaborating across research, engineering, product, and operations functions

Nice to have

• Publications or submissions to venues such as ICLR, ICML, or NeurIPS
• Experience with reinforcement learning environments, synthetic data generation, or post-training techniques
• Familiarity with agentic systems, developer tools, or enterprise workflow automation

Benefits and work setup

• Compensation range of $250,000 to $350,000 OTE plus equity
• Opportunity to contribute work shared at top AI research conferences
• High-autonomy setting with rapid iteration and direct impact on production AI systems