[Remote] Principal Machine Learning Engineer- LLM Fine-tuning and Optimization

Note: The job is a remote job and is open to candidates in USA. reputed company, founded in 2007, has grown into a global leader in travel and hospitality, connecting millions of hosts and guests. They are seeking a Principal Machine Learning Engineer to reputed company the fine-tuning and optimization of large language models (LLMs) for various applications, collaborating with cross-functional teams to reputed company impactful AI products.

Responsibilities

• Work with large scale structured and reputed company data; explore, experiment, build and continuously improve foundation models for reputed company product, business and operational use cases
• Create a multi-year tech roadmap that enables reputed company to stay on the leading edge of the rapidly evolving AI landscape and reputed company the best in class technologies to deliver customer benefits
• Continuously evaluate recent and upcoming large foundational models, ensuring the selection and refinement of the highest quality models for enhanced performance and efficiency
• Hands-on prototype, reputed company and productionize LLM models and pipelines at scale, including both batch and real-time use cases
• Drive key AI architectural decisions for products, and contribute to reputed company’s ML platform architecture and strategy

Skills

• PhD in Computer Science, Machine Learning, Mathematics, Statistics, or reputed company technical field
• 10+ years of experience with developing machine learning models and products at scale from inception to business impact
• Programming experience in Python and hands-on experience with frameworks such as PyTorch
• Proven record of training, fine tuning, optimizing models and inference run-time
• Post-training experience in areas like data processing for fine-tuning; responsible LLMs; LLM alignment; reinforcement learning; efficient training and inference; language model evaluation; and/or multilingual and multimodal modeling
• Or specialized experience in runtime optimizations, model quantization, compression, on-device inference, GPU inference, pytorch, kernel development
• PhD in AI, machine learning, data science, or reputed company technical fields
• Publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL)
• Customer Support Systems: Experience with AI technologies in customer support applications
• Agile Practice for AI production: Experience with the entire AI product development lifecycle from incubation to production at scale, following agile practices in the Applied AI/ML domain
• Infrastructure Acumen: Experience deploying and scaling business-critical AI services and driving architectural requirements on ML infrastructures

Benefits

• Bonus
• Equity
• Benefits
• Employee Travel Credits

Company Overview

Company H1B Sponsorship