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Llm Ml Rag Jobs in Seattle, WA (NOW HIRING)

Technical Product Manager, LLM/ML Domain

Seattle, WA · On-site

$190K - $219K/yr

They are seeking a Technical Product Manager to lead the development of their ML & LLM Ops ... RAG, fine-tuning, prompt management, evaluation frameworks, etc.) • Comfortable discussing ...

Applied Scientist II - Gen AI & LLM, PXT

Seattle, WA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Design and implement novel GenAI/LLM solutions using foundation models (e.g., Claude, GPT, LLaMA ... RAG, fine-tuning, RLHF, Transformer models, and AI Agents) - Experience with AWS AI/ML services ...

Senior Applied ML Engineer

Seattle, WA · Remote

$125K - $183K/yr

Develop and optimize CNN and LLM-powered models for computer vision, document extraction, and ... Familiarity with graph-based retrieval, RAG pipelines, or multimodal ML is preferred. Ready to Join?

Senior Staff ML Engineer

Seattle, WA · On-site

$118K - $163K/yr

We are seeking an accomplished Senior Staff ML Engineer who will serve as a technical leader for ... grade LLM-based AI agents, such as eval frameworks, agent tooling, RAG pipelines, prompt ...

Lead AI Engineer

Bellevue, WA · On-site

$115K - $151K/yr

... LLM-powered applications using state-of-the-art transformer models. • Build and optimize RAG ... ML) with production LLM systems • Good fundamentals of machine learning, deep learning and fine ...

ML Engineer (Senior)

Seattle, WA · On-site

$140K - $220K/yr

  • Medical

  • PTO

Generative AI and LLM-related capabilities (e.g., prompt engineering, RAG, fine-tuning, LangChain, model evaluation tooling) * MLOps and infrastructure automation (e.g., CI/CD for ML, Docker ...

AI Solution Architect

Bellevue, WA · On-site

$71 - $93.75/hr

... ML Cognitive Services Deep expertise in RAG architectures LLMs and a broad sound knowledge of ... LLM application design prompting orchestration tooluse grounding Handson with Azure AI services ...

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Llm Ml Rag information

See Seattle, WA salary details

$51.2K

$85.7K

$125.2K

How much do llm ml rag jobs pay per year?

As of Aug 20, 2026, the average yearly pay for llm ml rag in Seattle, WA is $85,693.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,600.00 and $99,000.00 per year, depending on experience, location, and employer.

What is an llm ml rag job?

LLM ML RAG jobs involve working with Large Language Models (LLMs), Machine Learning (ML), and Retrieval-Augmented Generation (RAG) systems. Professionals in these roles typically design, develop, and optimize AI systems that combine language models with retrieval techniques to improve accuracy, relevance, and factual grounding in generated outputs. These jobs often require expertise in natural language processing, deep learning, data engineering, and information retrieval. Key responsibilities might include integrating RAG pipelines, fine-tuning LLMs, and ensuring high-quality responses from AI applications.

What are some typical challenges faced when working on retrieval-augmented generation (RAG) systems in large language model (LLM) machine learning roles?

Professionals working on LLM ML RAG systems often encounter challenges such as ensuring the accuracy and relevancy of retrieved documents, managing latency for real-time queries, and seamlessly integrating retrieval mechanisms with generation models. Additionally, keeping up with evolving datasets and maintaining high-quality knowledge bases can be demanding. Collaboration with data engineers and domain experts is common to refine retrieval pipelines and optimize the end-to-end system.

What are the key skills and qualifications needed to thrive as an llm ml rag engineer, and why are they important?

To excel as an LLM ML RAG Engineer, you need a strong background in machine learning, natural language processing, and large language models, typically supported by a degree in computer science or a related field. Proficiency with tools and frameworks like Python, PyTorch/TensorFlow, Hugging Face Transformers, and vector databases (e.g., FAISS, Pinecone) is essential, along with experience in deploying and fine-tuning LLMs and integrating retrieval systems. Strong problem-solving skills, attention to detail, and the ability to collaborate with cross-functional teams distinguish top performers in this role. These skills ensure the effective development and deployment of advanced AI solutions that combine generative and retrieval capabilities for high-impact applications.

What is the difference between Llm Ml Rag vs Data Scientist?

AspectLlm Ml RagData Scientist
Required CredentialsMaster's or PhD in ML, AI, or related fields; certifications in ML frameworksDegree in Computer Science, Statistics, or related; certifications in data analysis or ML
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics, research, product development teams
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, tech, consulting firms
Common Search & ComparisonOften compared for ML specialization and research focusCompared for data analysis, modeling, and business insights

While both roles involve working with machine learning, Llm Ml Rag typically focuses on research and development of large language models, requiring advanced ML expertise. Data Scientists often work on analyzing data, building predictive models, and deriving insights for business decisions. The roles overlap in skills but differ in focus and application areas.

Infographic showing various Llm Ml Rag job openings in Seattle, WA as of August 2026, with employment types broken down into 1% Internship, 91% Full Time, 4% Part Time, and 4% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $85,693 per year, or $41.2 per hour.

Technical Product Manager, LLM/ML Domain

Agoda

Seattle, WA • On-site

$190K - $219K/yr

Full-time

Re-posted 10 hours ago


Job description

Job Summary:
Agoda is a travel technology company that is part of Booking Holdings, aiming to enhance travel experiences through innovation. They are seeking a Technical Product Manager to lead the development of their ML & LLM Ops platforms, facilitating the production and scaling of machine learning applications while ensuring seamless integration with AI-assisted development workflows.
Responsibilities:
• Define and evolve the product vision and roadmap for Agoda’s ML & LLM Ops platforms
• Shape how teams productionize ML models and LLM-powered applications
• Identify platform gaps, scalability constraints, and optimization opportunities
• Drive the evolution of our platform to support AI-native development workflows and coding agents
• Gather requirements from ML engineers, data scientists, backend engineers, and AI application teams
• Translate complex technical needs into clear product requirements and prioritization frameworks
• Proactively identify opportunities to reduce friction, improve reliability, and increase deployment velocity
• Balance experimentation flexibility with governance, safety, and cost efficiency
• Own features end-to-end: concept, specification, prioritization, implementation, and post-launch analysis
• Partner closely with engineering to balance platform scalability, performance, and technical debt
• Ensure platform capabilities support monitoring, evaluation, retraining, versioning, and observability of ML/LLM systems
• Drive adoption through documentation, training, and internal evangelism
• Collaborate with engineering to level up Agoda’s platforms to be more compatible with AI coding assistants and autonomous agents
• Ensure platform APIs, tooling, and abstractions enable meaningful AI-generated code contributions
• Help define guardrails and workflows that allow safe, reliable AI-assisted development
Qualifications:
Required:
• 5+ years of experience in ML engineering, data science, platform engineering, or a related technical domain
• 2+ years of technical product or program management experience in fast-paced, high-scale environments
• Experience working with ML Ops and/or LLM Ops concepts (model lifecycle, evaluation, monitoring, versioning, deployment pipelines)
• Strong understanding of ML systems and model lifecycle management
• Familiarity with LLM application patterns (RAG, fine-tuning, prompt management, evaluation frameworks, etc.)
• Comfortable discussing architecture, APIs, infrastructure trade-offs, and scalability concerns with senior engineers
• Strong analytical mindset with the ability to reason about system design, performance, and cost trade-offs
• Strong cross-functional leadership skills and ability to influence without authority
• Comfortable operating in ambiguity and rapidly evolving technological landscapes
• Excellent communication skills — able to translate between business, platform engineering, and AI application teams
• Proactive, structured thinker with a strong problem-solving mindset
• High ownership and bias for impact
Company:
Agoda is a digital travel platform that provides access to hotels and holiday properties including flights. It is a sub-organization of Booking Holdings. Founded in 2005, the company is headquartered in Singapore, SGP, with a team of 5001-10000 employees. The company is currently Late Stage.