Senior Data Scientist

About the Role

Are you eager to make a significant impact in the ever-evolving AI landscape? Join Snowpeak AI, a dynamic leader in AI innovation, as a Senior Data Scientist
. You’ll work alongside a top-tier AI team to harness data, advanced analytics, and cutting‑edge models to fuel strategic growth and deliver real‑world impact. This is your chance to lead data‑driven transformation, build intelligent systems, and push the boundaries of conversational AI and automation.

We seek a versatile expert with deep proficiency in conversational AI, LLMs
, agentic AI, retrieval systems
, and end‑to‑end ML development, combined with a relentless drive to learn, experiment, and solve complex problems. From designing RAG‑powered chatbots to securing data pipelines, you’ll own critical initiatives that power our AI‑enabled operators and customer solutions. Please note that we are a fully on‑site environment based in Irvine, CA.

• Design, build, and refine conversational AI systems using retrieval‑augmented generation (RAG), combining large language models (LLMs) with vector search and retrieval.
• Develop data ingestion and embedding pipelines to support scalable, efficient information retrieval.
• Fine‑tune and adapt LLMs for domain‑specific use cases, covering prompt engineering, instruction tuning, and low‑rank adaptation (LoRA).
• Integrate AI models into CRMs, workflow platforms and vendor management systems.
• Own the end‑to‑end development of machine learning algorithms, from data collection and feature engineering to model training, validation, and performance tuning.
• Research and prototype emerging ML architectures and retrieval strategies to enhance performance.
• Resolve and rerank RAG’s training material data for a single source of truth.
• Translate business requirements into robust, data‑driven technical solutions with measurable outcomes.
• Collaborate with engineering teams to deploy, scale, and monitor AI systems across the organization.
• Identify new opportunities to embed machine learning into business processes and workflows.
• Partner with Product, Marketing, Finance, Risk, and Operations to define and track key performance metrics.
• Continuously improve data pipelines for accuracy, accessibility, and scalability.
• Support cross‑functional data science initiatives and perform additional duties as needed.
• Other duties as assigned.

• Education: Bachelor’s degree in a quantitative or technical field;
  Master’s or Ph.D. preferred.
• 8+ years of professional experience in data science, AI, or applied machine learning.
• Proven experience in designing and building Voice AI systems and/or chatbots
  , including speech recognition, conversational agents, and real‑time dialogue models.
• Hands‑on proficiency with leading machine learning and deep learning frameworks
  , such as Lang Chain, Hugging Face, Tensor Flow, PyTorch, Keras, scikit‑learn, and pandas.
• 7+ years of strong programming expertise in Python/Pyspark and SQL
  , with proven experience deploying AI solutions in cloud environments (AWS or Google Cloud Platform).
• 2+ years of practical experience working with MCP,
  LLMs, generative AI, and conversational AI frameworks (e.g., Lang Chain, Lang Graph, RAG, Vector Databases, Auto Gen, CrewAI).
• 5+ years of specialization in at least one area of advanced modeling – predictive analytics, recommendation engine, reinforcement learning, natural language processing (NLP), or causal inference.
• 4+ years of experience translating complex AI and data science concepts into tangible business outcomes
  , including stakeholder engagement and value quantification.
• 4+ years leading end‑to‑end AI solution delivery
  , from data architecture and model orchestration to front‑end integration and user adoption.
• Demonstrated excellence in communication, storytelling, and customer engagement
  , with the ability to present technical insights in a clear and impactful manner.
• Experience developing agentic AI systems for conversational analytics, autonomous reporting, or intelligent decision support.
• Proven ability to design, train, and deploy machine learning models for real‑world applications.
• Strong expertise in data acquisition,…