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Staff Research Engineer, AI and Machine Learning — Remote in Vietnam
Lead research on frontier AI systems for Gramian Consulting, an IT professional services and engineering talent consultancy. Build experiments, prototypes, evaluations, and scalable machine learning innovations.
Сипаттама
- Examine the capabilities, limitations, and training techniques of frontier AI systems.
- Define research questions that guide AI products, platforms, and technical strategy.
- Investigate synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarking, and evaluation methods.
- Track advances in machine learning and identify opportunities for meaningful technical contributions.
- Create 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 reliable practices for data quality, reproducibility, experimental design, and evaluation.
- Advance research hypotheses into validated technical insights through iterative experimentation.
- Partner with Research, Engineering, Product, and Operations teams to apply findings in practice.
- Present technical discoveries to specialist and cross-functional audiences.
- Support technical reports, publications, open-source initiatives, workshops, or conferences when appropriate.
- Mentor engineers and researchers while contributing to technical reviews and discussions.
Талаптар
- 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.
- Solid machine learning fundamentals and practical experience designing experiments, training and evaluating models, or building AI systems.
- Research experience in 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 with the ability to implement, test, and rapidly iterate in research settings.
- Experience using contemporary AI and machine learning frameworks, tools, and research workflows.
- Strong 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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