Senior GenAI Scientist: LLMs, RAG & Production

Liberty Mutual Insurance; Seattle (WA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Hybrid work schedule

Job summary

Liberty Mutual Insurance's GenAI Research and Solution team seeks an individual contributor to design, fine-tune, and deploy GenAI solutions end to end—from research prototype to production service, using LLMs, RAG, and agentic orchestration on Kubernetes.

You will collaborate with engineers, researchers, and business partners, applying MLOps, data governance, and responsible AI practices to deliver scalable insurance domain capabilities.

Qualifications

• PhD/masters/bachelors with years of relevant AI research or engineering experience.
• Expertise with transformer models and fine-tuning techniques (LoRA/QLoRA).
• Hands-on GenAI pipelines, retrieval design, embedding strategies and vector search.
• Strong ML, statistics, experimental design and model evaluation metrics.
• Python and MLOps, Git repos, and ML experiment tracking (MLflow).
• PyTorch and GenAI ecosystem (HuggingFace, LangChain, LlamaIndex).
• Experience with workflow tools (Airflow, Luigi) for pipelines.
• Clear communication to diverse audiences; research-to-prod track record.
• Docker and CI/CD; Kubernetes deployment with Helm; GPU-backed services.
• GPU acceleration, distributed training, mixed precision and quantization.
• Multimodal models and cross-modal retrieval experience.
• Insurance data experience or regulated/Ai governance exposure.

Responsibilities

• Design, fine-tune and deploy language-model solutions from research to production.
• Fine-tune and distill LMs for domain-specific insurance tasks balancing accuracy, latency and cost.
• Build GenAI pipelines including RAG, corrective RAG and agentic orchestration.
• Develop scalable data and embedding pipelines with MLOps practices for reproducibility.
• Design evaluation suites and guardrails for grounded, safe GenAI use cases.
• Containerize and ship solutions on Kubernetes with production collaboration.
• Research new methods for training and evaluating generative models.
• Communicate findings through technical presentations and stakeholder reports.
• Participate in cross-functional groups and promote best practices in data science.

Skills

Transformer models

LoRA/QLoRA

GenAI pipelines

Python

PyTorch

HuggingFace

LangChain

Kubernetes

Docker

MLOps

Git/GitHub

MLflow

GPU acceleration

Distributed training

Vision-language

Education

Ph.D. in Statistics, CS, Math, Econ, Actuarial Science or related

Master's with 4+ years

Bachelor's with 6+ years

Tools

Git

Airflow

Luigi

MLflow

Kubernetes

GPU infrastructure

Job description

Liberty Mutual Insurance's GenAI Research and Solution team seeks an individual contributor to design, fine-tune, and deploy GenAI solutions end to end—from research prototype to production service, using LLMs, RAG, and agentic orchestration on Kubernetes.

You will collaborate with engineers, researchers, and business partners, applying MLOps, data governance, and responsible AI practices to deliver scalable insurance domain capabilities.