As a Senior Data Scientist on the AI Research & Reliability team, you will be a driving force in shaping the future of our company AI. You will act as a technical leader, working with cutting-edge LLMs, NLP, and machine learning to tackle our most ambiguous and complex customer problems. Working alongside Product, Engineering, and Data Scientist, you will spearhead the architecture, evaluation, and deployment of enterprise-grade AI capabilities at scale, while elevating the technical standards of the team.
You'll Own
The AI Technical Strategy: Lead the AI product lifecycle by partnering deeply with Product and Engineering to translate complex business needs into scalable, state-of-the-art AI solutions. Define the overarching AI approach, agent architectures, success metrics, and long-term technical vision before implementation.
Advanced Agentic Systems: Architect, build, and optimize complex sub-agents, tool-use mechanisms, retrieval systems, and memory architectures that power our company AI Agents. Establish industry-leading evaluation frameworks and benchmarks to rigorously measure and continuously improve workflow reliability.
Conversational Intelligence at Scale: Pioneer new NLP- and LLM-based methodologies to analyze massive, unstructured conversation datasets. You will design approaches that capture the deep intent, nuance, and strategic signals within human interactions.
Production-Grade Model Engineering: Architect highly robust and scalable Python pipelines. Set the standard for creating proprietary datasets, training/fine-tuning models, and integrating LLM-powered solutions into production environments serving millions of critical customer interactions.
You'll Solve
Complex Business Context Reasoning: Designing AI systems that can autonomously reason over vast, unstructured data spaces-combining conversations, CRM signals, and diverse data sources to uncover high-level insights and drive executive decision-making.
Architecting Intelligent Agent Experiences: Solving the hardest architectural challenges around long-term memory, multi-step reasoning, retrieval accuracy (RAG), and deterministic evaluation to ensure our company AI Agents deliver flawless, context-aware assistance.
Extracting Actionable Intelligence: Pushing the boundaries of applied NLP and LLMs to understand deep customer dynamics, foresee market trends, and transform raw, noisy conversations into structured, actionable intelligence across the customer lifecycle.
Advancing Applied AI Innovation: Leading experimentation with state-of-the-art AI approaches (advanced RAG architectures, parameter-efficient fine-tuning, complex agentic workflows) to solve novel product challenges and drastically improve AI quality and reliability.
You'll Impact
Global Sales Transformation: The foundational AI architectures you build will directly empower thousands of enterprises, fundamentally changing how revenue teams operate, strategize, and close deals.
Strategic Innovation to Implementation: You will bridge the gap between academic/bleeding-edge NLP developments and enterprise application, translating complex research into high-quality, scalable code that maintains our company's position as an AI industry leader.
You'll Own
The AI Technical Strategy: Lead the AI product lifecycle by partnering deeply with Product and Engineering to translate complex business needs into scalable, state-of-the-art AI solutions. Define the overarching AI approach, agent architectures, success metrics, and long-term technical vision before implementation.
Advanced Agentic Systems: Architect, build, and optimize complex sub-agents, tool-use mechanisms, retrieval systems, and memory architectures that power our company AI Agents. Establish industry-leading evaluation frameworks and benchmarks to rigorously measure and continuously improve workflow reliability.
Conversational Intelligence at Scale: Pioneer new NLP- and LLM-based methodologies to analyze massive, unstructured conversation datasets. You will design approaches that capture the deep intent, nuance, and strategic signals within human interactions.
Production-Grade Model Engineering: Architect highly robust and scalable Python pipelines. Set the standard for creating proprietary datasets, training/fine-tuning models, and integrating LLM-powered solutions into production environments serving millions of critical customer interactions.
You'll Solve
Complex Business Context Reasoning: Designing AI systems that can autonomously reason over vast, unstructured data spaces-combining conversations, CRM signals, and diverse data sources to uncover high-level insights and drive executive decision-making.
Architecting Intelligent Agent Experiences: Solving the hardest architectural challenges around long-term memory, multi-step reasoning, retrieval accuracy (RAG), and deterministic evaluation to ensure our company AI Agents deliver flawless, context-aware assistance.
Extracting Actionable Intelligence: Pushing the boundaries of applied NLP and LLMs to understand deep customer dynamics, foresee market trends, and transform raw, noisy conversations into structured, actionable intelligence across the customer lifecycle.
Advancing Applied AI Innovation: Leading experimentation with state-of-the-art AI approaches (advanced RAG architectures, parameter-efficient fine-tuning, complex agentic workflows) to solve novel product challenges and drastically improve AI quality and reliability.
You'll Impact
Global Sales Transformation: The foundational AI architectures you build will directly empower thousands of enterprises, fundamentally changing how revenue teams operate, strategize, and close deals.
Strategic Innovation to Implementation: You will bridge the gap between academic/bleeding-edge NLP developments and enterprise application, translating complex research into high-quality, scalable code that maintains our company's position as an AI industry leader.
Requirements:
M.Sc. or Ph.D. in an exact science field (Computer Science, Mathematics, Statistics, etc.). A deep academic or applied background in NLP or Machine Learning is required.
5+ years of industry experience in data science or machine learning, with a proven track record of taking complex AI and NLP solutions from concept to large-scale production.
Deep expertise in modern AI architectures, specifically advanced RAG, LLM fine-tuning, agentic workflows (e.g., LangChain, LlamaIndex), and robust LLM evaluation methodologies.
Exceptional Python engineering skills and mastery of ML/data ecosystem libraries (pandas, NumPy, scikit-learn, PyTorch, Transformers).
M.Sc. or Ph.D. in an exact science field (Computer Science, Mathematics, Statistics, etc.). A deep academic or applied background in NLP or Machine Learning is required.
5+ years of industry experience in data science or machine learning, with a proven track record of taking complex AI and NLP solutions from concept to large-scale production.
Deep expertise in modern AI architectures, specifically advanced RAG, LLM fine-tuning, agentic workflows (e.g., LangChain, LlamaIndex), and robust LLM evaluation methodologies.
Exceptional Python engineering skills and mastery of ML/data ecosystem libraries (pandas, NumPy, scikit-learn, PyTorch, Transformers).
This position is open to all candidates.
