Staff Research Engineer – Frontier AI, RL & Evaluation

Careerflow.ai’s Human Data Labs builds datasets and reinforcement-learning environments that support post-training for AI labs and enterprises. The Staff Research Engineer will investigate frontier AI systems, develop and evaluate research datasets, experiments, prototypes, and tooling, and translate findings into scalable AI applications.

Responsibilities:

• Investigate the capabilities, limitations, and training methods of frontier AI systems
• Formulate research questions that inform products, platforms, and technical strategy
• Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation
• Stay current with advances in machine learning and identify opportunities for meaningful technical contributions
• 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 strong practices for experimental rigor, data quality, reproducibility, and interpretation
• Iterate quickly from initial hypotheses to validated technical insights
• Collaborate with Research, Engineering, Product, and Operations teams
• Translate research findings into improvements for products, platforms, and AI capabilities
• Identify which ideas are ready to move from exploration into scalable, real-world applications
• Communicate technical findings clearly to both specialized and cross-functional audiences
• Share findings through technical reports, publications, open-source work, workshops, or conferences where appropriate
• Contribute to research culture through technical discussions, peer review, mentorship, and collaboration
• Represent thoughtfully within the broader AI research community