Senior, Data Scientist - GenAI; Sunnyvale​/Bentonville

Overview

Chance to work on financial data for complex problems/challenges. Utilize LLMs/Genai systems and architectures to build and deploy state-of-the-art Genai systems. Our team collaborates closely with Finance teams to enhance financial planning and strategic decision-making through cutting‑edge data‑driven solutions. We specialize in a range of initiatives that provide actionable insights into trends and patterns and leverage Generative AI (Genai) to produce concise, insightful summaries that empower decision‑makers.

By integrating these innovative approaches, we strive to drive efficiency, accuracy, and impactful outcomes in financial operations.

• Develop data science systems and tools for retail and e‑commerce applications.
• Leverage LLMs to summarize and build large‑scale applications.
• Establish cross‑functional relationships to maintain a win‑win situation for the corporation.
• Collaborate with various product stakeholders and business owners to formulate and product ionize a solution.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal‑opportunity/affirmative‑action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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• Master's degree or PhD in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 5 years’ experience in analytics related field.
• Experience with training and inference of large‑scale AI models such as Large Language Models (LLMs), multimodal models, and reasoning models.
• Knowledge of advanced model optimization techniques, including quantization, pruning, distillation, Low‑Rank Adaptation (LoRA), and Parameter‑Efficient Fine‑Tuning (PEFT) for cloud deployment.
• Solid understanding of LLMs and Genai ecosystems, including GPT, LLaMA, Mistral, Claude, Gemini, AWS Sonnet, and related frameworks/tools.
• Hands‑on experience with RAG (Retrieval‑Augmented Generation), AI agent development, and frameworks such as Lang Chain, Lang Graph, etc. Experience with big data processing and feature engineering using Spark.
• Experience with training machine learning models through Cloud Services including Google Cloud Platform and Microsoft Azure.
• Hands‑on experience of designing and training large DL models on GPU farm.