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AI​/ML Engineer

Job in Bellevue, King County, Washington, 98009, USA
Listing for: Cacheflow
Full Time position
Listed on 2026-06-01
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 140000 - 160000 USD Yearly USD 140000.00 160000.00 YEAR
Job Description & How to Apply Below

Team Charter:

The Data team is the engine of intelligence  mission is to transform massive amounts of marketplace data into seamless, safe, and personalized experiences that empower millions of people to connect and prosper. We bridge the gap between complex algorithms and real-world customer impact across search, trust & safety, and personalization.

About the role:

AI is transforming how millions of people buy, sell, and connect on Offer Up - and this role is at the center of making that happen. As an AI Engineer on the Data team, you will own the production systems — from agentic workflows and RAG pipelines to LLM integrations - that turn our marketplace intelligence into real customer experiences. From enhancing search ranking and personalization to powering fraud detection and generative AI features, your work will have a company-wide impact and be felt by millions of users every day.

The Data team reports into the broader engineering organization and directly influences Offer Up’s most critical product surfaces.

We are looking for an AI Engineer to join our Data team
. This team is tasked with building the core intelligence - supporting search ranking, recommendation engines, fraud detection, and generative AI features - that is critical to Offer Up's success as the leading local marketplace. You will be part of a cross-functional team that includes Data Engineering and Data Science, serving as the bridge that turns research and models into shipped, production-grade AI systems.

What we love about this role:

  • Breadth of Impact:
    You won't be siloed; you will build AI systems that drive results across Search & Discovery, Trust & Safety, Advertising, and core Personalization.
  • Modern AI Stack:
    Work with agentic frameworks (Lang Chain, Lang Graph), RAG architectures, and LLM APIs to solve real marketplace problems.
  • Production Ownership:
    You will build, ship, and own AI features end-to-end, from design through deployment.
  • Collaborative Environment:
    Work alongside Senior Data Scientists and Engineers, positioning you at the intersection of research and production.

In this role, you will

  • Design and build agentic AI systems and RAG pipelines for production features across the marketplace.
  • Integrate LLMs into product experiences across search, categorization, communication, and trust & safety.
  • Partner with Data Scientists and Engineers to turn research into shipped products.

Here’s more of what you will get to do:

  • Impact on Product:
    Deliver the next generation of Search, Personalization, and Trust & Safety features powered by reliable, production-quality AI systems.
  • Impact on Company:
    Directly contribute to key business KPIs (conversion, retention, fraud reduction) by turning data science insights into shipped capabilities.
  • Critical Projects:
    Production RAG pipelines for intelligent discovery; agentic workflows for marketplace automation; tooling and infrastructure for rapid, safe LLM deployment.

You’ll thrive in this role if you have:

  • 2-4 years building and deploying AI/ML systems in production.
  • 2+ years professional Python development.
  • Hands‑on experience with agentic frameworks (Lang Chain, Lang Graph, or similar) including function calling and tool‑use design.
  • Practical experience building RAG systems (vector search, semantic chunking, rerankers).
  • Experience with LLM APIs, prompt engineering, and structured outputs.
  • Proficiency with async Python (asyncio, streaming) and Pydantic.
  • Strong SQL skills for large‑scale data systems.
  • Bachelor’s in CS, Math, Statistics, or related field (or equivalent experience).
  • Collaborative mindset and strong communication skills.

Helpful, but not required: [nice to haves]

  • LLMOps tooling: evals (Ragas, Deep Eval), observability (Lang Smith, Arize Phoenix), guardrails (NeMo).
  • Cloud deployment of AI services (AWS preferred).
  • Graph

    RAG or knowledge graph integration (Neo4j/Falkor

    DB).
  • ReAct, Plan-and-Solve, or multi‑agent collaboration patterns.

Compensation Range: $140,000 - $160,000

Offer Up offers a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. Individual salaries within our ranges are…

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