Rust Developer

We are seeking a skilled Rust Developer with a strong background in systems programming and a keen interest in machine learning and human-computer interaction. The successful candidate will contribute to the advancement of large language models (LLMs) by engaging in Reinforcement Learning from Human Feedback (RLHF) tasks. This role involves building tools to facilitate human feedback and providing insights to improve the performance of LLMs.

Key Responsibilities:

• Participate in RLHF tasks, offering human feedback on LLM outputs to guide model training.
• Evaluate responses generated by LLMs, identify areas for improvement, and provide qualitative feedback.
• Collaborate with data scientists and ML engineers to ensure feedback is accurately integrated into the model's learning process.
• Work with cross-functional teams to understand and define requirements for the RLHF process.
• Provide insights on systematically incorporating human feedback into model training and improvement.
• Document processes and best practices for human feedback integration in LLM training.
• Stay informed about advancements in reinforcement learning, LLMs, and human-computer interaction.
• Experiment with new tools and methods to enhance feedback collection and integration in RLHF tasks.

Technical Skills:

• 3+ years of experience in Rust development, with a solid understanding of systems programming, performance optimization, and concurrency.
• Experience with CI/CD pipelines and version control systems (e.g., Git) with at least 3 years of hands-on experience.
• Familiarity with machine learning concepts, particularly reinforcement learning, is a strong plus.
• Experience in human-computer interaction, user feedback systems, or related domains is advantageous.

Analytical Skills:

• Strong problem-solving skills and the ability to analyze and optimize RLHF tasks.
• Experience in evaluating and providing constructive feedback on AI/ML outputs.

Soft Skills:

• Excellent communication skills with the ability to articulate feedback and collaborate with diverse teams.
• A detail-oriented approach, committed to ensuring high-quality contributions to model training.
• A proactive mindset, eager to learn and adapt to new techniques in a rapidly evolving field