Description

Design and implement behavioral logic and decision-making frameworks for autonomous AI agents, focusing on LLM tuning and performance evaluation.

This role is on-site.

Responsibilities

• Develop and maintain evaluation metrics and testing frameworks to assess agent performance.
• Analyze LLM performance and implement tuning techniques including fine-tuning, prompt engineering, and RLHF.
• Contribute to AI platform infrastructure to support the deployment and scaling of intelligent agents.
• Collaborate with research scientists to explore novel approaches in agentic AI and LLM applications.
• Document design specifications, implementation details, and experimental results.

Required Skills

• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 5+ years of experience in software systems design, preferably in AI agents or robotics.
• Strong programming skills in Python and relevant AI/ML libraries.
• Hands-on experience with Large Language Models (LLMs).
• Experience with Hugging Face Transformers, PyTorch, or TensorFlow.
• Knowledge of LLM tuning and Vertex AI.
• Solid understanding of reinforcement learning principles and RLHF.
• Strong analytical and debugging skills.

Preferred Skills

• Experience building agents using the Google Gemini Vertex tool set.
• Preference for Gemini LLMs.

Key Skills

Education

Master's degree