Roman Darker

Q: What is Roman Darker email address?

Email Roman Darker at roman.darker@dataannotation.tech. This email is the most updated Roman Darker's email found in 2026.

Q: How to contact Roman Darker?

To contact Roman Darker send an email to roman.darker@dataannotation.tech. (updated on May 15, 2025)

AI Data Specialist at DataAnnotation | New York City Metropolitan Area

About Roman Darker

Roman Darker is a highly skilled AI Data Specialist at DataAnnotation, where he leverages his extensive background in software engineering and machine learning to drive innovative data annotation solutions. In his current role, Roman focuses on optimizing data pipelines and developing sophisticated annotation workflows that enhance the quality and accuracy of training datasets for large language models (LLMs) and other AI systems. His expertise in reinforcement learning techniques, particularly Reinforcement Learning with Human Feedback (RLHF), enables him to fine-tune models for improved performance and alignment with human expectations. Roman’s proficiency in engineering prompts and modifying AI-generated outputs ensures that models produce reliable and contextually appropriate results, which is critical in high-stakes applications such as natural language understanding and conversational AI.

Roman’s technical skill set, including experience with AWS cloud infrastructure, SQL, MongoDB, and TypeScript, allows him to design scalable, efficient data annotation platforms that meet diverse client needs. His background in building caching tools with Node.js and React, combined with his knowledge of frameworks like Redux.js and Webpack, provides him with a strong foundation in full-stack development and system optimization. Additionally, Roman’s experience in testing and debugging—using tools like Jest and his ability to mock environments across multiple languages—ensures the robustness and reliability of AI data pipelines. His industry insights and hands-on expertise make him a valuable asset in advancing AI data annotation processes, ultimately contributing to the development of more accurate, fair, and efficient AI models.

Roman Darker Work