LLM Research Engineer

LLM Research Engineer

Summary:

Our client is seeking a highly skilled Machine Learning Engineer to join their team and focus on the design, training, and optimization of large language models (LLMs). In this role, you ll work at the forefront of generative AI, developing state-of-the-art models that push the boundaries of natural language understanding and generation. If you are passionate about transformers, NLP, and large-scale AI systems, this is an exciting opportunity to make an impact on the next generation of AI applications.

Responsibilities:

• Design, train, and fine-tune large language models (LLMs) such as GPT, LLaMA, and PaLM for diverse applications.
• Conduct research on cutting-edge NLP and machine learning techniques to improve model performance.
• Explore advancements in transformer architectures, multi-modal models, and emergent AI behaviors.
• Collect, clean, and preprocess large-scale text datasets from diverse sources.
• Develop and apply data augmentation techniques to improve data quality while ensuring ethical AI standards and bias mitigation.
• Optimize model architecture to enhance accuracy, efficiency, and scalability.
• Implement techniques to reduce latency, memory footprint, and inference time for real-time applications.
• Collaborate with MLOps teams to deploy models into production environments using Docker, Kubernetes, and cloud infrastructure.
• Build robust evaluation pipelines with metrics such as accuracy, perplexity, BLEU, and F1 score.
• Continuously test for bias, fairness, and robustness across diverse datasets.
• Conduct A/B testing to validate model improvements in real-world applications.
• Stay current with the latest advancements in generative AI, transformers, and NLP research.
• Contribute to research papers, patents, and open-source projects.
• Present findings at conferences and internal knowledge-sharing sessions.

Qualifications:

• Advanced degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• Strong programming skills and hands-on experience with deep learning frameworks (TensorFlow, PyTorch, JAX).
• Experience with transformer-based models (e.g., GPT, BERT, RoBERTa, LLaMA).
• Expertise in natural language processing (NLP) and sequence-to-sequence models.
• Familiarity with Hugging Face libraries and OpenAI APIs.
• Proficiency with MLOps tools including Docker, Kubernetes, and CI/CD pipelines.
• Strong understanding of distributed computing and GPU acceleration (CUDA).
• Knowledge of reinforcement learning and RLHF (Reinforcement Learning with Human Feedback).

Location: Mountain View, CA

Duration: 1 year +

Hourly Range: $110-121 DOE

To Apply: Submit your resume to