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Llm Knowledge Graph Jobs in Redmond, WA (NOW HIRING)

... LLM-based systems in production. * Experience adding intelligence to internal processes and ... and knowledge graph integration. * Ability to collaborate deeply across teams and co-create ...

Build and maintain LLM evaluation frameworks - including automated regression suites, human ... Knowledge graph or graph database experience (Neo4j, Amazon Neptune) * AWS certification (Solutions ...

... both structured knowledge graph data and unstructured web data) and Summarization as well as ... Description In this role, you will work on LLM based question answering and Apple Intelligence ...

The Applied AI Engineer will be responsible for building knowledge extraction, mapping, and ... hybrid or graph-based search, and caching strategies. • Experience with LLM orchestration ...

... Knowledge Packs). * Accelerate AI accuracy by 60% by designing and deploying a Concept Graph that ... Modern LLM Orchestration: Direct, practical experience building sophisticated applications using ...

... Knowledge Packs). * Accelerate AI accuracy by 60% by designing and deploying a Concept Graph that ... Modern LLM Orchestration: Direct, practical experience building sophisticated applications using ...

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Llm Knowledge Graph information

See Redmond, WA salary details

$45.9K

$70.9K

$107K

How much do llm knowledge graph jobs pay per year?

As of Aug 27, 2026, the average yearly pay for llm knowledge graph in Redmond, WA is $70,905.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,100.00 and $77,800.00 per year, depending on experience, location, and employer.

What is the difference between Llm Knowledge Graph vs Data Scientist?

AspectLlm Knowledge GraphData Scientist
Required CredentialsKnowledge of NLP, graph databases, machine learningStatistics, programming, data analysis
Work EnvironmentResearch labs, AI companies, tech firmsCorporate, consulting, research institutions
Industry UsageAI, knowledge management, semantic webBusiness analytics, predictive modeling

While both roles involve data and machine learning, Llm Knowledge Graph specialists focus on building interconnected knowledge bases using NLP and graph technologies, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap in AI projects but serve different core functions within organizations.

What are popular job titles related to Llm Knowledge Graph jobs in Redmond, WA?

For Llm Knowledge Graph jobs in Redmond, WA, the most frequently searched job titles are:

What job categories do people searching Llm Knowledge Graph jobs in Redmond, WA look for?

The top searched job categories for Llm Knowledge Graph jobs in Redmond, WA are:

Staff / Sr. Machine Learning Engineer, AI, Search & Knowledge Platforms

Seattle, WA • On-site


Apple Inc.
Computer and Electronic Product Manufacturing • 10K+ employees

8.1

Company rating: 8.1 out of 10

Based on 678 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

People enjoy working here

Good employer

Recommended by students


$175 - $308.50/hr

Other

Medical, Dental, Retirement

Posted 21 days ago


Job description

Staff / Sr. Machine Learning Engineer, AI, Search & Knowledge Platforms

Seattle, Washington, United States Machine Learning and AI

Imagine what you could do here. At Apple, great ideas quickly become extraordinary products, services, and customer experiences. Bring passion and dedication to your work, and there’s no telling what you could accomplish. Do you want to make Siri and Apple products smarter for our users? The Information Intelligence teams are building groundbreaking technology for algorithmic search, machine learning, natural language processing, and artificial intelligence. The features we build are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Within this organization, our group focuses on web-scale extraction and enrichment, transforming raw web content into structured, high-quality knowledge that powers Apple’s intelligent experiences. We design scalable extraction algorithms, develop advanced web data deduplication techniques, and apply machine learning to process trillions of records and petabytes of data. We also build and maintain Apple’s Knowledge Graph, integrating diverse data sources into a unified representation of the world knowledge. We’re looking for a Machine Learning Engineer with deep expertise in large-scale data and ML infrastructure. You will build and optimize pipelines that extract, process, and serve data artifacts while advancing the ML frameworks and tooling that underpin Apple’s knowledge and search systems.

Description

Join a dynamic team within Apple's Information Intelligence Infrastructure organization that designs, builds, and operates large-scale systems powering search and AI experiences for billions of users. We develop distributed, data-intensive infrastructure that processes web data at global scale, enabling extraction, enrichment, and knowledge graph construction across diverse content such as HTML, PDF, and other unstructured formats.

Responsibilities
  • Build and optimize large-scale extraction and enrichment pipelines that transform raw web data into structured knowledge powering Siri, Spotlight, Safari, and other Apple experiences.
  • Design pipelines that leverage large language models, advanced NLP, and entity linking frameworks to identify, deduplicate, and contextualize information from the open web.
  • Optimize extraction infrastructure for cost, throughput, and reliability including model serving and batch ML workloads.
  • Develop ML classifiers for data quality, deduplication, and content filtering across billions of records.
  • Improve extraction quality to produce high-fidelity training corpora for Apple's foundation models, directly improving reasoning and grounding capabilities.
Minimum Qualifications
  • Bachelor’s degree or higher in Computer Science or related technical field
  • 3+ years of experience in software engineering or ML engineering
  • Experience with Golang, Java, Scala, or Python
  • Background in computer science: algorithms, data structures, and distributed systems
  • Experience working in a cloud-native environment such as AWS
  • Experience working with large-scale data processing pipelines (Spark, Cassandra, etc.)
  • Experience with micro-service architecture in a containerized environment (Docker, Kubernetes, etc.)
  • Experience with machine learning workflows, including feature engineering, training, evaluation, deployment and serving
Preferred Qualifications
  • Experience with training and fine-tuning large language models
  • Experience with optimizing ML training and serving performance, including GPU tuning, batch size optimization, and multi-node scheduling
  • Familiarity with Nvidia TensorRT-LLM, vLLM, Nvidia Triton Server, or similar inference frameworks.
  • Experience with NLP, information extraction, or web data systems.
  • Excellent interpersonal skills, able to work independently as well as in a team

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $175,000 and $308,500, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace.

Learn about reasonable accommodations for job applicants.

Apple accepts applications to this posting on an ongoing basis.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976


What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

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