AI Research Engineer

Summary

Prolific is reshaping the landscape of AI development by focusing on the quality and diversity of human-generated data. They are seeking a Research Engineer to conduct innovative research in AI evaluation methodologies, alignment techniques, and synthetic data generation, bridging the gap between cutting-edge AI research and practical applications.

Responsibilities

• Lead independent research projects in AI evaluation methodologies, alignment techniques, and synthetic data generation
• Design and implement novel evaluation frameworks for LLMs and agent systems that are grounded in human data
• Contribute to the academic AI community through publications and open-source contributions
• Stay at the forefront of AI research and pioneer innovative approaches to tackle pressing open challenges in the field
• Design and conduct rigorous experiments to study AI models and systems with sound methodological approaches
• Develop scalable frameworks for systematic evaluation of model behaviours and capabilities
• Create tools and frameworks that transform research insights into practical applications
• Build infrastructure to support large-scale research experiments when needed
• Apply knowledge of model fine-tuning, optimization techniques, distillation, and other ML engineering practices to support research goals
• Work closely with ML engineers, data scientists, and product teams to translate research insights into practical applications
• Mentor team members on advanced AI concepts and emerging research directions
• Communicate complex technical concepts to diverse stakeholders

Skills

• 5+ years of engineering experience with significant AI/ML focus
• Demonstrated research experience through publications, open-source contributions, or impactful projects
• Strong engineering fundamentals and experience implementing AI systems in production environments
• Deep knowledge of LLM evaluation methodologies, alignment techniques, and model optimization approaches
• Experience with model fine-tuning, adapters, quantization, and distillation frameworks
• Self-motivation and ability to define and pursue research directions independently
• Excellent understanding of current challenges in AI safety, reliability, and alignment
• Strong communication skills and ability to explain complex research concepts clearly
• Passion for staying current with the rapidly evolving AI research landscape

Qualifications

Must Haves

• 5+ years of engineering experience with significant AI/ML focus
• Demonstrated research experience through publications, open-source contributions, or impactful projects
• Strong engineering fundamentals and experience implementing AI systems in production environments
• Deep knowledge of LLM evaluation methodologies, alignment techniques, and model optimization approaches
• Experience with model fine-tuning, adapters, quantization, and distillation frameworks
• Self-motivation and ability to define and pursue research directions independently
• Excellent understanding of current challenges in AI safety, reliability, and alignment
• Strong communication skills and ability to explain complex research concepts clearly
• Passion for staying current with the rapidly evolving AI research landscape

Benefits

• Competitive salary
• Benefits
• Remote working