Data Scientist II
New
USAFull-TimeMiddle
Salary120,000 - 145,000 USD per year
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Job Details
- Experience
- Master's degree plus two (2) years of experience as a data scientist.
- Required Skills
- PythonSQLPrompt EngineeringLangChain
Requirements
- Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Operations Research, Industrial Engineering, or a directly related field.
- Two (2) years of experience as a data scientist.
- Programming experience in Python.
- Developing and designing Large Language Model (LLM) interaction flows, evaluation frameworks, or advanced prompting strategies.
- Partnering with engineering teams to deploy GenAI/LLM solutions into production.
- Experience with Generative AI, including Large Language Models, Prompt Engineering, Retrieval Augmented Generation (RAG), and Semantic Search/Vector Databases.
- Researching and implementing advanced prompting techniques, such as Chain-of-Thought or Few-Shot prompting.
- Experience with dialogue systems and context management.
- Hands on experience with LLM Orchestration Frameworks, such as LangChain / LangGraph.
- Experience with Transformer architectures, specifically understanding Attention mechanisms, Context Windows, and Tokenization constraints.
- Experience with SQL.
Responsibilities
- Propose, plan, and execute applied research initiatives that will make a real-world impact on Conversational AI using Large Language Models (LLMs) within a commercial setting.
- Use expert knowledge of Transformer architecture mechanics (Attention, Tokenization, Embeddings) to consistently find the most effective, efficient, stable, explainable, and elegant prompting and orchestration approaches.
- Utilize modern LLM inference and retrieval pipelines.
- Analyze large scale conversational datasets for RAG (Retrieval-Augmented Generation) optimization.
- Bring research-inspired prompt strategies to life within production systems.
- Create durable, flexible scientific evaluation and experimentation capabilities for non-deterministic model outputs.
- Present findings on model behavior and context efficacy in ways that inform and guide business and product strategy.
- Work closely with other scientists.
- Stay current with the rapidly evolving state of Generative AI.
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