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 transparent, 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 qualified 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.
Solid Python programming skills and ability to implement, test, and iterate quickly in a research environment.

📌 Staff Research Engineer Frontier Ai, Rl & Evaluation Gurugram (India)
🏢 Crossing Hurdles
📍 India