LLM Research Engineer IV

Pay: $110-130/hour W2

Benefits

• Health insurance
• Vision insurance
• Dental insurance
• Life insurance
• Disability insurance

Benefits are available after a qualification period.

Responsibilities

• Design, train, and fine-tune large language models (e.g., GPT, LLaMA, PaLM) for various applications.
• Conduct research on cutting-edge techniques in natural language processing (NLP) and machine learning 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 implement data augmentation techniques to improve training data quality.
• Ensure data is free from bias and aligned with ethical AI standards.
• Optimize model architecture to improve accuracy, efficiency, and scalability.
• Implement techniques to reduce latency, memory footprint, and inference time for real-time applications.
• Collaborate with MLOps teams to deploy LLMs into production environments using Docker, Kubernetes, and cloud platforms.
• Develop robust evaluation pipelines to measure model performance using key metrics like accuracy, perplexity, BLEU, and F1 score.
• Continuously test for bias, fairness, and robustness of language models across diverse datasets.
• Conduct A/B testing to evaluate model improvements in real-world applications.
• Stay updated with the latest advancements in generative AI, transformers, and NLP research.
• Contribute to research papers, patents, and open-source projects.
• Present findings and insights at conferences and internal knowledge-sharing sessions.

Requirements

• Master’s degree with a minimum of 3+ years experience post-graduation or Bachelor’s degree with a minimum of 5+ years experience post-graduation.
• Advanced degree in Computer Science, Artificial Intelligence, Data Science, or a related field welcome.
• Strong programming skills.
• Proficiency with deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Hands-on 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.
• Experience with MLOps tools like Docker, Kubernetes, and CI/CD pipelines.
• Strong understanding of distributed computing and GPU acceleration using CUDA.
• Knowledge of reinforcement learning and RLHF (Reinforcement Learning with Human Feedback).

Schedule

This is an onsite role, located in Mountain View, CA.

W2 candidates only.

About Us

The Fountain Group is a nationwide staffing firm with over 80 Fortune 100-500 clients. Since 2001, TFG has maintained a consistent standard of excellence, and our work is broadly recognized every year through numerous industry performance awards. Our success is a team effort.