Overview
The AI / ML Engineer position focuses on leveraging large language models (LLMs) to enhance cutting-edge generative AI systems. The successful candidate will collaborate with researchers to develop the infrastructure and frameworks necessary for advancing LLM capabilities, while working directly with tools and environments for experimentation and model optimization.
Responsibilities
- Design and build tools, methods, and infrastructure for LLM development.
- Collaborate with researchers to identify and resolve weaknesses in agent-generated code.
- Develop scalable frameworks for annotation, training, and model experimentation.
- Apply agentic design principles to enhance LLM reasoning, reliability, and autonomy.
- Conduct hands-on work with Python, LLMs, and LLaMA models, optimizing performance through experiments.
- Procure and manage coding environments such as Jupyter Notebook or Google Colab.
Requirements
- 4+ years of experience in Machine Learning / AI, particularly with LLMs or generative AI systems.
- Strong hands-on experience with LLM agents and related frameworks.
- Proficient in Python, with experience in PyTorch or TensorFlow.
- Familiarity with agentic design principles and architectures based on LLaMA.
- Demonstrated capability in debugging and problem-solving within ML contexts.
- Experience managing large-scale ML experiments and compute environments.
- Master’s or PhD in Computer Science, AI, ML, or related field is required.
- Bonus: Track record in research (publications, Kaggle Master) and backend/frontend development experience.