Applied AI Research Engineer - LLM Specialist

Core Responsibilities

• Design and implement LM experiments from a data science perspective, including data preparation, model selection, and results analysis
• Develop and execute fine-tuning strategies for various LM architectures
• Establish robust evaluation frameworks and benchmarking methodologies for model performance
• Lead prompt engineering initiatives and develop systematic approaches to prompt optimization
• Develop scalable Python-based solutions for model training and deployment

Required Qualifications

• Advanced degree in Computer Science, Machine Learning, or related field
• Deep understanding of LM architectures, including transformers, Mamba, and Jamba
• Deep understanding of modern trends and ecosystem of AI in general and LMs in particular
• Proven experience with LM fine-tuning and optimization techniques
• Demonstrated expertise in developing evaluation metrics and benchmarking frameworks for LLMs
• Advanced prompt engineering skills with systematic approach to optimization
• Expert-level Python programming skills
• Experience with major deep learning frameworks (PyTorch, TensorFlow, or JAX)

Desired Qualifications

• Experience with reinforcement learning, particularly in the context of language models
• Familiarity with Small Language Models (SLMs), their training, optimizations and applications
• Experience in AI Agent development and research
• Experience with quality synthetic data generation and augmentation
• Knowledge of efficient CPU deployment strategies for language models
• Experience with RAG, embedding & effective chunking strategies
• Experience with multi-modality & MoE
• Experience with multi-lingual datasets and LMs and understanding of their inherit challenges
• Expertise in building and maintaining ML pipelines