Staff Research Engineer - AI & Machine Learning

About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Role
We are looking for a Staff Research Engineer to advance research and practical innovation in frontier AI systems. You will investigate high-impact questions, design rigorous experiments, build research-grade prototypes and tooling, and collaborate across Research, Engineering, Product, and Operations teams.
The role focuses on areas including synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and AI evaluation. You will help translate promising research ideas into scalable applications and improvements to AI products and systems.
SENIORITY: Staff level — 7+ years
Key Responsibilities
Investigate the capabilities, limitations, and training methods of frontier AI systems.
Formulate research questions that inform AI 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 develop clear, evidence-based conclusions.
Establish rigorous practices for data quality, reproducibility, experimental design, and evaluation.
Iterate rapidly from research hypotheses to validated technical insights.
Collaborate with Research, Engineering, Product, and Operations teams to translate findings into practical applications.
Communicate technical findings to both specialized and cross-functional audiences.
Contribute to technical reports, publications, open-source projects, workshops, or conferences where appropriate.
Mentor engineers and researchers and contribute to technical discussions and peer review.
Requirements
Ph.D. or Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, or a closely related technical field.
7+ years of professional experience, including significant research engineering experience in machine learning or frontier AI systems.
Strong foundations in machine learning and hands-on experience designing experiments, training models, evaluating models, or developing AI systems.
Demonstrated research experience in at least one of the following:
Synthetic or agentic data generation
Reinforcement learning or post-training
Model understanding
AI evaluation
AI benchmarks
AI agents or tool-using systems
Strong Python programming skills with the ability to implement, test, and iterate quickly in research environments.
Experience with modern AI/ML frameworks, tooling, and research workflows.
Strong scientific judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making.
Excellent technical communication skills and ability to work independently across research and engineering teams.

Work arrangement
No