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 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.

- Strong Python programming skills and ability to implement, test, and iterate quickly in a research environment.

📌 Staff Research Engineer ( Frontier AI, RL & Evaluation) (Gurugram)
🏢 Crossing Hurdles
📍 Gurugram