Staff Engineer, AI Model

We are seeking a highly motivated and skilled Model Development Engineer to join our rapidly growing AI team in Morrisville, NC. You will play a critical role in the training of large language models (LLMs), large vision models (LVMs), and large multimodal models (LMMs), including fine-tuning and reinforcement learning. This is a challenging yet rewarding opportunity to contribute to cutting-edge research and development in generative AI. You'll be working with a collaborative team to push the boundaries of what's possible with AI models and deploy them into innovative products.

Responsibilities:

• Design, implement, and evaluate training pipelines for large generative AI models, encompassing multiple stages of post-training.
• Data: Design, implement, and evaluate data augmentation pipelines to increase the diversity and robustness of training datasets, improving model performance, particularly in low-data regimes.
• Model evaluations: Develop and implement model evaluation pipeline for LLMs
• Supervised Fine-tuning (SFT): Developing and executing SFT strategies for specific tasks.
• RLHF: Developing and leveraging RLHF algorithms in model training such as DPO and KTO
• Reinforcement Learning (RL): Exploring RL training strategies, sampling, reward function design and etc. to apply large scale RL to model training
• Quantization: Implement and evaluate model quantization techniques to reduce model size and accelerate inference speed, balancing precision loss with performance gains for deployment across diverse hardware platforms.
• Low-Rank Adaptation (LoRA): Utilizing techniques for efficient fine-tuning of large language models, balancing performance and resource constraints, and tailoring model performance for downstream tasks well.
• Experiment with various training techniques, hyperparameters, and model architectures to optimize performance and efficiency.
• Develop and maintain data pipelines for processing and preparing training data.
• Stay up-to-date with the latest advancements in large language models, training techniques, and related technologies.
• Collaborate with other engineers and researchers to design, implement, and deploy AI-powered products.
• Contribute to the development of internal tools and infrastructure for model training and evaluation.

Qualifications:

• Ph.D degree in Computer Science, Machine Learning, or a related field.
• Strong programming skills in Python and experience with deep learning frameworks like Pytorch, Transformers.
• Solid understanding of machine learning principles, including supervised learning, unsupervised learning, and reinforcement learning.
• Proven experience in designing and conducting experiments, analyzing data, and drawing meaningful conclusions.
• Familiarity with large language models, transformer architectures, and related concepts.
• Experience with data processing tools and techniques (e.g., Pandas, NumPy).
• Experience with distributed training frameworks (e.g., DeepSpeed, Megatron-LM).
• Excellent communication, collaboration, and problem-solving skills.

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