Staff Research Engineer ( Frontier AI, RL & Evaluation)

Crossing Hurdles; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Crossing Hurdles is seeking a senior AI researcher to investigate frontier AI capabilities and training methods. You will formulate research questions guiding product strategy and collaborate with cross-functional teams to translate findings into practical applications.

The role emphasizes designing experiments, developing evaluation frameworks, and advancing synthetic data generation, reinforcement learning, and model understanding in a fast-paced research environment.

Qualifications

• Advanced degree in AI/ML or related field.
• 7+ years of relevant research experience.
• Strong Python and ML experimentation skills.
• Experience with synthetic or agentic data generation or RL.

Responsibilities

• Investigate capabilities, limitations, and training methods of frontier AI systems.
• Formulate research questions informing products, platforms, and technical strategy.
• Explore synthetic/agentic data generation, RL, post-training, model understanding, benchmarks, AI evaluation.
• Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks.
• Train, test, and evaluate models using modern AI and ML tools.
• Analyze results and derive evidence-based conclusions.
• Establish rigorous practices for experimental design, data quality, reproducibility, and interpretation.
• Collaborate with Research, Engineering, Product, and Operations to translate findings into practical applications.

Skills

Python

Research engineering

Machine Learning

AI research

Experiment design

Education

Masters or PhD in AI/ML/CS

Job description

Role & responsibilities

• Investigate the capabilities, limitations, and training methods of frontier AI systems.
• Formulate research questions that inform products, platforms, and technical strategy.
• Explore approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and AI evaluation.
• Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks.
• Train, test, and evaluate models using modern AI and machine learning tools.
• Analyze experimental results and draw clear, evidence-based conclusions.
• Establish rigorous practices for experimental design, data quality, reproducibility, and interpretation.
• Collaborate with Research, Engineering, Product, and Operations teams to translate research findings into practical applications.

Preferred candidate profile

• Masters or PhD in Artificial Intelligence, Machine Learning, Computer Science, or a closely related technical field.
• Exceptional equivalent research experience may also be considered.
• 7+ years of professional experience with significant research engineering experience in machine learning or frontier AI systems.
• Strong foundations in machine learning with practical experience designing experiments, training models, evaluating models, or developing AI systems.
• Demonstrated research experience in synthetic or agentic data generation, reinforcement learning, post-training, model understanding, AI evaluation, benchmarks, AI agents, or tool-using systems.
• Strong Python programming skills and ability to implement, test, and iterate quickly in a research environment.