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Llm Knowledge Graph Jobs in California (NOW HIRING)

Clera

Founding Engineer

San Francisco, CA · On-site

$150K - $220K/yr

Design, build, and operate core infrastructure powering a people-data and AI agent platform, including APIs, LLM-powered workflows, scraping systems, and large-scale knowledge graph architecture.

Clera

Founding Engineer

San Francisco, CA · On-site

$150K - $220K/yr

Design, build, and operate core infrastructure powering a people-data and AI agent platform, including APIs, LLM-powered workflows, scraping systems, and large-scale knowledge graph architecture.

Spark Tek Inc

AI Engineet

San Jose, CA · On-site

$134K - $161K/yr

... knowledge graph integration). • Explore and implement Agentic AI patterns (e.g., supervisor vs ... with LLM fine-tuning strategies for domain-specific applications. • Collaborate on data ...

ArangoDB

Developer Relations

San Francisco, CA · On-site +1

$160 - $200/day

GraphRAG and knowledge-graph communities, AI engineering meetups, framework ecosystems, and ... You have hands-on, production experience with LLM applications and retrieval: RAG pipelines ...

Afresh

Staff AI Platform Engineer

San Francisco, CA · Hybrid

$168K - $253K/yr

Design and operate the knowledge graph and ontology that capture how grocery data relates. * Build ... Build LLM-powered agents (tool-use, multi-step reasoning, orchestration) and the serving ...

Afresh

Senior AI Platform Engineer

San Francisco, CA · Hybrid

$156K - $211K/yr

Design and operate the knowledge graph and ontology that capture how grocery data relates. * Build ... Build LLM-powered agents (tool-use, multi-step reasoning, orchestration) and the serving ...

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Llm Knowledge Graph information

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.

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Senior Machine Learning Engineer, Apple Search & Knowledge Platforms

Apple

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Re-posted 15 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

The AI, Search & Knowledge Platforms team builds amazing products and services for Apple's customers while serving as a foundational partner to teams across Apple. The team delivers world-class AI, search, and knowledge systems powering Siri, Apple Intelligence, Safari, and iMessage, and operates the foundational platforms and infrastructure that keep these intelligent experiences running at hyperscale.
As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data and unstructured web data) and Summarization as well as developing fundamental building blocks needed for Artificial Intelligence. This involves developing sophisticated machine learning and large language models (LLMs) to understand user queries, retrieve and rank relevant documents across multiple sources and synthesize information across documents to provide user with a direct answer that best satisfies their intent and information seeking needs. Additionally, you will research and develop the state-of-the-art LLMs for summarizing personal data such as emails, messages, and notifications.
You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain specific Large Language Models for various tasks and applications in Apple's AI powered products and conduct applied research to transfer the cutting edge research in generative AI to production ready technologies.
Description
As a member of our fast-paced group, you'll have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for highly motivated machine learning engineers and researchers having strong machine learning and deep learning fundamentals with hands-on experience in fine-tuning deep learning and large language models.
Minimum Qualifications
2+ years of experience working with Deep learning or LLM model development for various NLP tasks and RAG applications including prompt engineering, training data collection and generation, model fine-tuning and model evaluation.
Experience working with Python and at least one of the deep learning frameworks such as TensorFlow, PyTorch, or JAX.
Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Preferred Qualifications
PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
4+ years of experience with large-scale model training, optimization, and deployment
One or more scientific publications in various conferences and journals
Outstanding communication and interpersonal skills with ability to work with cross-functional teams.
1+ year of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more of the following areas:
Supervised Fine-tuning (SFT) with Rejection Sampling
Preference-based fine-tuning techniques (e.g RLHF, Reward model, DPO, PPO, GRPO etc.)
Parameter efficient fine-tuning techniques (e.g LoRA)
Hallucination reduction and factual accuracy improvements
Designing and implementing safety guardrails

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

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

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