Overview
Full Time
Skills
Functional Design
Artificial Intelligence
Integrated Circuit
Python
Natural Language Processing
Data Science
Information Engineering
Internet Explorer
Generative Artificial Intelligence (AI)
Research
Semantic Search
Prompt Engineering
Information Retrieval
RESTful
Linux
Unix
Software Engineering
Agile
Code Review
Testing
Job Details
Do you love creating elegant solutions to highly complex challenges? Do you intrinsically see the importance in every detail? As part of our Silicon Technologies group, you'll help build AI-driven solutions that solve pressing business challenges. You'll ensure Apple products and services can seamlessly and efficiently handle the tasks that make them beloved by millions. Joining this group means you'll be responsible for crafting and building the technology that fuels Apple's devices. We are looking for an individual who is passionate about joining Apple's engineering team as an NLP Solutions Software Engineer to enable building generative AI applications for our domains.
Description In this highly visible role, your primary responsibilities will include: - Developing LLM components for use in generative AI applications. - Collaborating with our internal multi-functional design teams as well as the AIML organization at Apple to understand domain-specific needs and tailor AI solutions to these domains. - Serving as the point of contact for customers, resolving technical issues, and providing insights on LLM infrastructure improvements. - Enabling the organization to leverage data and drive efficiency in chip delivery.
Minimum Qualifications
Preferred Qualifications
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 .
Description In this highly visible role, your primary responsibilities will include: - Developing LLM components for use in generative AI applications. - Collaborating with our internal multi-functional design teams as well as the AIML organization at Apple to understand domain-specific needs and tailor AI solutions to these domains. - Serving as the point of contact for customers, resolving technical issues, and providing insights on LLM infrastructure improvements. - Enabling the organization to leverage data and drive efficiency in chip delivery.
Minimum Qualifications
- Proficiency in Python programming
- Hands-on-experience in NLP and Data Science principles (ie. Indexing knowledge, pre-processing data, or fine-tuning models).
- Familiarity with current Gen AI research in one of the following areas: RAG, Semantic Search, Agents, or Prompt Engineering
- Minimum requirement of BS and 3+ years of relevant industry experience
Preferred Qualifications
- Experience in designing and implementing information retrieval systems using embeddings (e.g., MiniLM), vector stores (e.g., Milvus, Qdrant), or similarity match & ranking techniques.
- Proficiency in articulating technical and architectural challenges in a precise manner.
- Experience collaborating with partners to develop and iterate on solutions.
- Designed and optimized RESTful services.
- Comfort within Linux/Unix environments.
- Understanding of software engineering practices (agile, code review, automated builds, regressions testing).
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 .
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.