Software Engineer - LLM Workflows - Apps
AppleGermany7 hours ago
Full-timeEngineering, Information Technology
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Summary
Imagine what you could do here. At Apple, new ideas have a way of becoming great products very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.nnThe Apps Engineering team, empowering millions of writers, musicians, filmmakers, photographers, designers and creators worldwide, is seeking a software engineer to work on Large Language Model interfaces, fine-tuning and deployment. You’ll work on cutting-edge AI applications, helping deploy LLM workflows across diverse environments while maintaining Apple’s high standards for quality, performance, and creative ethics.
Description
Make a difference. As a Software Engineer specializing in LLM Workflows on the Apps Engineering team, you'll collaborate daily with machine learning researchers, application engineers, framework engineers, and product designers to work on advanced language models and task automation. nnYour work will span the entire development lifecycle, from defining data requirements and evaluation frameworks to deploying LLM workflows across tools and applications. This role requires expertise in prompt engineering, retrieval-augmented generation, and model fine-tuning to create intelligent, context-aware experiences.
Minimum Qualifications
Experience fine-tuning Large Language Models for specific domains or tasks, alongside integrating LLMs and deploying fine-tuned adapters.nExperience developing software applications using Python, Swift, or C++.nExperience with REST APIs, JSON, and working with LLM services (e.g., OpenAI APIs).nExperience building data collection and evaluation pipelines for machine learning systems.
Preferred Qualifications
BS/MS in Computer Science, Machine Learning, or related technical field, or 3 years of equivalent work experience.nExperience with prompt engineering and optimization techniques for LLMs.nExperience implementing retrieval-augmented generation (RAG) systems.nExperience developing agentic workflows and orchestration systems.nExperience with local model deployment and on-device LLM inference.nExperience with Apple's Foundation Model framework or similar ML frameworks.nExperience collaborating with framework engineers to optimize ML infrastructure.nExperience working with creators, audio/video production, or creative software applications.
Imagine what you could do here. At Apple, new ideas have a way of becoming great products very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.nnThe Apps Engineering team, empowering millions of writers, musicians, filmmakers, photographers, designers and creators worldwide, is seeking a software engineer to work on Large Language Model interfaces, fine-tuning and deployment. You’ll work on cutting-edge AI applications, helping deploy LLM workflows across diverse environments while maintaining Apple’s high standards for quality, performance, and creative ethics.
Description
Make a difference. As a Software Engineer specializing in LLM Workflows on the Apps Engineering team, you'll collaborate daily with machine learning researchers, application engineers, framework engineers, and product designers to work on advanced language models and task automation. nnYour work will span the entire development lifecycle, from defining data requirements and evaluation frameworks to deploying LLM workflows across tools and applications. This role requires expertise in prompt engineering, retrieval-augmented generation, and model fine-tuning to create intelligent, context-aware experiences.
Minimum Qualifications
Experience fine-tuning Large Language Models for specific domains or tasks, alongside integrating LLMs and deploying fine-tuned adapters.nExperience developing software applications using Python, Swift, or C++.nExperience with REST APIs, JSON, and working with LLM services (e.g., OpenAI APIs).nExperience building data collection and evaluation pipelines for machine learning systems.
Preferred Qualifications
BS/MS in Computer Science, Machine Learning, or related technical field, or 3 years of equivalent work experience.nExperience with prompt engineering and optimization techniques for LLMs.nExperience implementing retrieval-augmented generation (RAG) systems.nExperience developing agentic workflows and orchestration systems.nExperience with local model deployment and on-device LLM inference.nExperience with Apple's Foundation Model framework or similar ML frameworks.nExperience collaborating with framework engineers to optimize ML infrastructure.nExperience working with creators, audio/video production, or creative software applications.
Key Skills
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