Description

Key Skills: Large Language Models (LLMs), Deep Learning, Machine Learning, Natural Language Processing, Speech Processing, Computer Vision, Python, Reinforcement Learning, Data Analysis, Research

Good to Have Skills: Experience with multimodal systems, LLM evaluation and tooling, modern LLM architectures, SFT, DPO, RLHF and RLAIF techniques, A/B testing frameworks, cross-team collaboration, mentoring experience, scientific publications, and community engagement in AI research.

Roles & Responsibilities:

• Analyze, understand, and model customer behavior and customer experience based on large-scale data.
• Build novel online and offline evaluation metrics and methodologies for multimodal personal digital assistants.
• Fine-tune and post-train LLMs using advanced techniques like SFT, DPO, and Reinforcement Learning for location and language specific performance.
• Quickly experiment and set up experimentation frameworks for agile model and data analysis or A/B testing.
• Contribute through industry-first research to drive innovation forward in the field of applied AI.
• Drive cross-team scientific strategy and influence partner teams on LLM evaluation frameworks and post-training methodologies.
• Lead end-to-end delivery of scientifically complex solutions from research to production including reusable science components.
• Serve as a scientific thought leader, communicating solutions clearly to partners, stakeholders, and senior leadership.
• Actively mentor junior scientists and contribute to the broader scientific community through publications and engagement.

Experience Required: Senior level experience in applied science with expertise in machine learning, speech and/or natural language processing, and modern LLM architectures. Experience working in fast-paced environments and delivering impactful solutions while iterating based on user feedback

Key Skills

Education

Any Graduate