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About the Role

This role advances Conversational AI through research and experimentation with Large Language Models (LLMs) in real-world customer interactions. Responsibilities include designing and executing applied research, developing prompting and orchestration strategies, optimizing LLM inference and retrieval pipelines, and analyzing conversational datasets for RAG system improvement. The role also involves building experimentation frameworks, translating model insights into product and business strategy, and staying current with Generative AI advancements.

Responsibilities

Propose, plan, and execute applied research initiatives for Conversational AI using LLMs in a commercial setting.
Develop effective, efficient, stable, explainable, and elegant prompting and orchestration approaches using Transformer architecture knowledge.
Utilize modern LLM inference and retrieval pipelines.
Analyze large-scale conversational datasets for RAG optimization.
Implement research-inspired prompt strategies in production systems.
Create scientific evaluation and experimentation capabilities for non-deterministic model outputs.
Present findings on model behavior and context efficacy to inform business and product strategy.
Collaborate with other scientists.
Stay current with Generative AI advancements.

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.
Two (2) years of experience in programming in Python.
Two (2) years of experience in developing and designing Large Language Model (LLM) interaction flows, evaluation frameworks, or advanced prompting strategies.
Two (2) years of experience in partnering with engineering teams to deploy GenAI/LLM solutions into production.
One (1) year of experience with Generative AI, including Large Language Models, Prompt Engineering, Retrieval Augmented Generation (RAG), and Semantic Search/Vector Databases.
One (1) year of experience in researching and implementing advanced prompting techniques, such as Chain-of-Thought or Few-Shot prompting.
One (1) year of experience with dialogue systems and context management.
One (1) year of experience with LLM Orchestration Frameworks, such as LangChain / LangGraph.
One (1) year of experience with Transformer architectures, specifically understanding Attention mechanisms, Context Windows, and Tokenization constraints.
One (1) year of experience with SQL.

Skills

Python programming
Large Language Model (LLM) interaction flows
LLM evaluation frameworks
Advanced prompting strategies
GenAI/LLM solution deployment
Generative AI
Prompt Engineering
Retrieval Augmented Generation (RAG)
Semantic Search/Vector Databases
Chain-of-Thought prompting
Few-Shot prompting
Dialogue systems
Context management
LLM Orchestration Frameworks (LangChain, LangGraph)
Transformer architectures (Attention mechanisms, Context Windows, Tokenization constraints)
SQL

Location

USA
Remote

Work Type

Fully Remote
Remote-First Model

Experience Level

Two (2) years of experience as a data scientist
Two (2) years of experience in programming in Python
Two (2) years of experience in developing and designing Large Language Model (LLM) interaction flows, evaluation frameworks, or advanced prompting strategies
Two (2) years of experience in partnering with engineering teams to deploy GenAI/LLM solutions into production
One (1) year of experience with Generative AI, including Large Language Models, Prompt Engineering, Retrieval Augmented Generation (RAG), and Semantic Search/Vector Databases
One (1) year of experience in researching and implementing advanced prompting techniques, such as Chain-of-Thought or Few-Shot prompting
One (1) year of experience with dialogue systems and context management
One (1) year of experience with LLM Orchestration Frameworks, such as LangChain / LangGraph
One (1) year of experience with Transformer architectures, specifically understanding Attention mechanisms, Context Windows, and Tokenization constraints
One (1) year of experience with SQL

Education Level

Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Operations Research, Industrial Engineering, or a directly related field

Salary/Compensations

$120,000 to $145,000 USD

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
Wellness Resources
Employee Assistance Program (EAP)
401(k) Retirement Plan with 4% employer match
HSA Plans
FSA Plans
Employee Stock Purchase Program (ESPP)
Basic life insurance
Supplemental life insurance
Accidental Death & Dismemberment (AD&D) insurance
Long-term disability insurance coverage
Short-term disability insurance coverage
Legal plan
Identity theft protection plan
Critical illness supplemental insurance
Internal professional development resources
Flexible Paid Time Off (PTO)
Paid Public Holidays
Generous Parental Leave Policy
Maternity/paternity support
Fertility services
Dedicated WeWork space access

About the Company

LivePerson (NASDAQ: LPSN) is a leader in trusted enterprise conversational AI and digital transformation.
The company's award-winning Conversational Cloud platform connects leading brands with millions of consumers.
Powers nearly a billion conversational interactions monthly, providing rich data analytics and safety tools.
Unlocks the power of conversational AI for better business outcomes.
Named the #1 Most Innovative AI Company in the world by Fast Company.
Celebrates diversity, empowering its team to forge impactful conversations globally.
Embraces uniqueness, fosters constant growth, and empowers individual success.
Recognized by Fast Company, Newsweek, and BuiltIn for being a top innovative, beloved, and remote-friendly workplace.
Recognized by Gartner as a leader in the Conversational AI space.

Equal Opportunity

Committed to fostering an inclusive workplace and proud to be an Equal Opportunity Employer (EOE).
Believes that diverse perspectives drive innovation.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other characteristics protected by US Federal, State, or Local law.
Dedicated to the accessibility needs of applicants and employees.
Provides reasonable accommodations to job applicants with disabilities.
Applicants requiring a reasonable accommodation for any part of the application or hiring process should inform their recruiting contact upon initial connection.