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Gramian Consulting Group

Staff Research Engineer - AI & Machine Learning

Posted 4 Hours Ago
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Remote
Hiring Remotely in India
Senior level
Remote
Hiring Remotely in India
Senior level
Conduct frontier AI research across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarking, and evaluation. Design experiments, datasets, prototypes, tooling, and evaluation frameworks; train and assess models; analyze results; ensure rigor and reproducibility; and translate findings into scalable AI products. Collaborate across research, engineering, product, and operations teams, communicate technical insights, contribute to publications or open source, and mentor engineers and researchers.
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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.

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