Research Engineer

What you'll do

• Develop AI-powered workflows and build data pipelines for model training and evaluation.
• Design benchmarks, fine-tune and train LLMs, and improve model performance and compute efficiency.
• Research techniques such as reinforcement learning, retrieval-augmented generation, and autonomous reasoning, and turn findings into scalable solutions.

What they ask for

• Experience with foundation models, including fine-tuning, prompt engineering, and optimization.
• Proficiency in Python, Go, or C++, with experience in distributed systems and cloud infrastructure.
• Experience with large-scale data pipelines, embeddings, vector databases, or search.
• Understanding of transformers, deep learning, and self-supervised learning.

Nice to have

• Experience with Reinforcement Learning (RLHF/RLCEF), Retrieval-Augmented Generation (RAG), or multi-agent AI systems.

Tools

Python, Go, C++, GPT-4, Llama, Gemini

AI focus

Build and evaluate AI models and workflows for production engineering and reliability, including LLM fine-tuning, reinforcement learning, retrieval-augmented generation, and autonomous reasoning.