Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
Job Overview
Come join the LLM Dev and Evaluation team as a Staff Data Scientist.
We are building the Intuit Foundational LLM, as part of a proprietary Generative AI operating system (GenOS) platform.
Responsibilities
How youll lead
You will leverage cutting-edge techniques in natural language processing (NLP) and large language models (LLMs)
to work with diverse, multi-modal data types and massive scales, using proprietary Intuit data to unlock insights. Apply advanced model fine-tuning, transfer learning, prompt engineering, few-shot learning, and data augmentation methods to build both predictive and generative models, fueling innovation across Intuit products.
You will apply deep LLM expertise and independent judgment to collaborate with cross-functional teamsdata engineers, ML architects, product managers, and business analyststo develop high-performance LLM pipelines. Design and execute research strategies for optimizing model architecture, prompt optimization, tokenizer customization, data curation, noise reduction, and hyper-parameter tuning to meet Intuits complex and large-scale data challenges.
You will provide actionable, real-time guidance to stakeholders on utilizing LLM models, embeddings, and vector databases to meet critical business needs. Advise teams on deploying LLM-driven insights for unique business cases, empowering them to make informed, data-driven decisions at scale and stay aligned with advancements in generative AI, reinforcement learning, and self-supervised learning.
You will lead the end-to-end development of LLM workflows, encompassing hypothesis generation, model fine-tuning, data preprocessing, A/B testing, visualization, and interpretability methods. Foster a continuous feedback loop for model retraining, precision tuning, and seamless deployment, ensuring alignment with shifting data scales and complex multi-domain applications.
You will empower business leaders with interpretability tools and a strategic understanding of LLM outputs. Provide essential entrepreneurial guidance on deploying actionable insights and scaling models to maximize ROI and drive impact. Help Intuit fully exploit cutting-edge AI capabilities, integrating emerging advancements in transformers, attention mechanisms, and multi-task learning.
Requirements: What it takes
Strong NLP and LLM knowledge: experience with NLP techniques and LLM technologies for the last 1.5 years
Passion for Emerging AI Technologies - Demonstrated interest in cutting-edge advancements in NLP, LLMs, generative AI, machine learning, and deep learning, with a focus on staying ahead of the latest developments in transformer architectures, self-supervised learning, and model fine-tuning.
Robust Technical Expertise in Data Science and LLMs - Strong foundational understanding of the data science principles underlying LLMs, including tokenization, embeddings, pre-training and fine-tuning methods, data augmentation, and prompt engineeringnot just training models.
Global Collaboration:- Proven ability to collaborate with cross-functional teams and partners worldwide to deliver highly complex, LLM-focused projects that address unique business challenges.
Adaptability and Independence: Maturity, quick learning abilities, and the flexibility to thrive in a fast-paced, innovation-driven environment, adapting to evolving LLM techniques and tools.
Exceptional Communication Skills: strong verbal and written communication skills, with the ability to lead discussions, conduct professional presentations, and explain LLM and AI concepts to non-technical
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