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Gramian Consulting is a remote-first consulting firm focused on engineering, data, and AI talent. It helps organizations expand technical capacity through talent augmentation, recruiting, dedicated teams, and contractor management, while providing services such as LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure. The firm also supports individual career development through mentorship and education programs covering career readiness, interview preparation, and international market orientation. Its work combines hands-on engineering and recruiting experience to help clients build technical teams and apply AI to business needs.
Staff Research Engineer, AI and Machine Learning (Remote Contract) | Gramian Consulting
Lead frontier AI research spanning model evaluation, experimentation, and prototype development. Gramian Consulting delivers IT professional services and engineering talent solutions.
Description
- Examine the capabilities, limitations, and training approaches of frontier AI systems
- Define research questions that shape AI products, platforms, and technical direction
- Investigate synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation
- Track machine learning advances and identify opportunities for meaningful technical contributions
- Build research-grade datasets, experiments, prototypes, tools, and evaluation frameworks
- Train, test, and assess models with current AI and machine learning technologies
- Interpret experimental findings and draw evidence-based conclusions
- Develop standards for data quality, reproducibility, experimental design, and evaluation
- Advance research hypotheses into validated technical insights through iterative investigation
- Partner with Research, Engineering, Product, and Operations teams to apply findings in practice
- Present technical results to specialist and cross-functional audiences
- Support technical reports, publications, open-source work, workshops, or conferences when relevant
- Mentor engineers and researchers while participating in technical reviews and peer discussions
Requirements
- A Ph.D. or master’s degree in artificial intelligence, machine learning, computer science, or a closely related technical discipline
- At least 7 years of professional experience, including substantial research engineering work in machine learning or frontier AI systems
- Deep machine learning fundamentals and practical experience designing experiments, training and evaluating models, or building AI systems
- Research experience with synthetic or agentic data generation, reinforcement learning or post-training, model understanding, AI evaluation, benchmarks, or AI agents and tool-using systems
- Advanced Python skills for rapid implementation, testing, and iteration in research settings
- Experience using contemporary AI and machine learning frameworks, tools, and research practices
- Sound scientific judgment regarding experimental rigor, data quality, reproducibility, and evidence-based decisions
- Excellent technical communication skills and the ability to work independently across research and engineering teams
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