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Intern Knowledge Graph Jobs in California (NOW HIRING)

Preferred: knowledge of quantum optics, photonic hardware, switch network design, optimization, graph theory. U.S. Intern Hourly Pay Rate Chart Education level COMPLETED Hourly Rate Housing/Commuter ...

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Knowledge of quantum information is required. Familiarity with some of the following is desirable ... graph states, stabilizer methods, quantum error-correcting codes, linear optical quantum computing ...

Knowledge of quantum information is required. Familiarity with some of the following is desirable ... graph states, stabilizer methods, quantum error-correcting codes, linear optical quantum computing ...

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 ...

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Intern Knowledge Graph information

What are Intern Knowledge Graphs?

Intern Knowledge Graphs refer to structured data models that represent the relationships and attributes of information relevant to internship programs, roles, and experiences. These graphs help organizations and educational institutions organize and analyze data about interns, such as their skills, projects, mentors, and learning outcomes. By leveraging knowledge graphs, companies can improve internship matching, track progress, and gain insights into intern performance and program effectiveness. This technology is especially useful in large organizations managing multiple internship opportunities or research projects.

What is the difference between Intern Knowledge Graph vs Intern Data Analyst?

AspectIntern Knowledge GraphIntern Data Analyst
Required CredentialsBasic understanding of data structures, some knowledge of graph databasesBasic statistics, Excel, SQL knowledge
Work EnvironmentTech-focused, research-driven, often in AI or data science teamsBusiness or research settings, analyzing datasets and generating reports
Employer & Industry UsageTech companies, AI firms, research institutionsFinance, marketing, healthcare, and other industries

Intern Knowledge Graph roles typically focus on understanding and working with graph databases and data structures, often within tech or research environments. Intern Data Analyst positions involve analyzing datasets, creating reports, and supporting decision-making across various industries. While both roles require foundational data skills, the Intern Knowledge Graph role emphasizes graph database knowledge, whereas the Intern Data Analyst role centers on data analysis and reporting.

What types of projects can an Intern Knowledge Graph expect to work on, and how do these projects contribute to larger organizational goals?

As an Intern Knowledge Graph, you can expect to work on projects involving the design, development, and maintenance of knowledge graphs, which help structure and connect data across the organization. Tasks may include data integration, ontology development, and writing queries to extract meaningful insights from large datasets. These projects often support initiatives in artificial intelligence, data analytics, and search optimization, making your contributions valuable to multiple teams. You'll likely collaborate with data scientists, software engineers, and business analysts, gaining exposure to both technical and strategic aspects of knowledge management.

What are the key skills and qualifications needed to thrive as an Intern in Knowledge Graphs, and why are they important?

To thrive as a Knowledge Graph Intern, you need a strong foundation in computer science fundamentals, data structures, and familiarity with semantic web concepts, often supported by coursework or a related degree in computer science or information science. Experience with technical tools such as SPARQL, RDF, graph databases (like Neo4j), and possibly Python or Java is typically expected. Strong analytical thinking, problem-solving abilities, and effective communication skills help you collaborate with teams and translate complex ideas clearly. These competencies enable interns to contribute meaningfully to knowledge graph projects, ensuring data is structured, connected, and accessible for organizational use.
What are the most commonly searched types of Knowledge Graph jobs in California? The most popular types of Knowledge Graph jobs in California are:
What are popular job titles related to Intern Knowledge Graph jobs in California? For Intern Knowledge Graph jobs in California, the most frequently searched job titles are:
What cities in California are hiring for Intern Knowledge Graph jobs? Cities in California with the most Intern Knowledge Graph job openings:
Senior Machine Learning Engineer, Apple Search & Knowledge Platforms

Senior Machine Learning Engineer, Apple Search & Knowledge Platforms

Apple

Santa Clara, CA

$175K - $308K/yr

Full-time

Medical, Dental, Retirement

Re-posted 8 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 670 frontline employees who took The Breakroom Quiz

5th 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.","responsibilities":"Conduct research and development on state-of-the-art deep learning and large language models for various tasks and applications in Apple’s AI-powered products
Developing, fine-tuning, and evaluating domain-specific Large Language Models for various NLP tasks including summarization, question answering, search relevance/ranking, entity linking and query understanding problems
Conducting applied research to transfer the cutting edge research in generative AI to production ready technologies
Understanding product requirements, translate them into modeling tasks and engineering tasks
Stay up to date with the latest advancements and research in deep learning and large language models
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
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.
Pay & Benefits
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.

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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