Frontier AI Research Engineer

turing; Palo Alto (CA); On-site; USD 250,000 - 400,000; Full time

Benefits offered by this job

Equity

Job summary

Turing is seeking Research Engineers to advance frontier AI systems, develop data and RL environments, and push practical innovations across synthetic data, training, evaluation, and benchmarks.

You’ll work at the intersection of research and engineering, designing rigorous experiments, building prototypes, and collaborating with Research, Engineering, Product, and Operations teams to translate ideas into scalable applications.

Qualifications

• PhD or Master’s in artificial intelligence, machine learning, computer science, or related field; exceptional equivalent research experience considered.
• Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling.
• Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post‑training, AI understanding, evaluation, or benchmarks.

Responsibilities

• Conduct research on frontier AI systems and formulate questions informing products and strategy.
• Build and evaluate research systems, datasets, experiments, prototypes, tooling, and evaluation frameworks.
• Translate research findings into practical improvements for products, platforms, and AI capabilities across teams.
• Contribute to the research community through reports, publications, open‑source work, and conferences.

Skills

ML fundamentals

Experiment design

Model evaluation

Research engineering

Communication

Education

PhD or Master’s degree in AI/ML/CS or related

Tools

Python

AI tooling

Job description

Turing is seeking Research Engineers to advance frontier AI systems, develop data and RL environments, and push practical innovations across synthetic data, training, evaluation, and benchmarks.

You’ll work at the intersection of research and engineering, designing rigorous experiments, building prototypes, and collaborating with Research, Engineering, Product, and Operations teams to translate ideas into scalable applications.