Job description
Our client is an innovative startup focused on developing open-source infrastructure that optimizes Large Language Model (LLM) applications through a continuous feedback loop. Their mission is to enhance the performance and efficiency of LLMs in real-world applications by creating cutting-edge tools and frameworks that seamlessly integrate with AI workflows.
Role Overview:
As an AI Researcher, you will play a key role in advancing their AI infrastructure and optimizing LLM applications. Your research will directly impact the effectiveness and scalability of LLMs in diverse use cases. This is an exciting opportunity for someone passionate about AI, open-source development, and building foundational infrastructure that enables the future of AI applications.
Responsibilities:
- Conduct research to improve the performance, scalability, and adaptability of LLM applications.
- Design and implement novel AI algorithms for optimizing LLMs through feedback loops.
- Collaborate with engineering teams to integrate research insights into production systems.
- Contribute to the open-source ecosystem by publishing research, developing tools, and sharing best practices.
- Analyze experimental results, iterate on prototypes, and optimize algorithms to meet performance goals.
- Stay up-to-date with the latest developments in AI, machine learning, and LLM technologies.
Qualifications:
- PhD or equivalent experience in AI, Machine Learning, or related field.
- Strong background in deep learning, natural language processing (NLP), and reinforcement learning.
- Experience with large-scale LLM architectures and optimization techniques.
- Proficiency in programming languages such as Python, TensorFlow, or PyTorch.
- Familiarity with open-source development and contributing to collaborative research projects.
- Excellent problem-solving skills and a passion for cutting-edge AI research.
