GenAI Engineering Lead - Apple Services Engineering
GenAI Engineering Lead - Apple Services Engineering
Posted on :
08-09-2025
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1 Vacancy
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Job Description
As a core member of our GenAI team you will lead transformative progress in the application large-scale foundational models with a strong focus on bringing to life new and innovative customer experiences that delight millions of customers across the mission is to push the boundaries of planning reasoning and agentic intelligence. You will design and implement large-scale AI/ML solutions integrating the latest state of the art research in our global collaborating with partner teams across Apple youll contribute by sharing your experience delivering architectural proposals that account for international market needs and maintaining an ethos of continual learning from your counterparts. This position is at the intersection of Generative AI Machine Learning and Software ideal candidate will have expertise with LLMs and deep learning models machine learning lifecycle management data generation methods model training & validation coupled with strong fundamentals and passion in software engineering and system architecture.
- Comprehensive experience leading ML/AI initiatives and teams in a fast-paced environment particularly in generative AI traditional ML and knowledge graphs
- Demonstrated ability to work cross-functionally and influence product development through a combination of technical leadership and user-centered thinking.
- Hands-on experience designing and building GenAI platforms that allow users to experience AI applications supporting features like agent orchestration multi-step reasoning prompt engineering RAG integration and model selection
- Strong programming skills in Python Java or similar languages with an emphasis on AI/ML systems development and platform engineering. Experience with TensorFlow PyTorch or Keras
- B.S M.S. or PhD Degree in Computer Science/Engineering or equivalent work experience
- Experience working in multinational or distributed teams especially across Europe and the U.S.
- In-depth understanding of large language models (LLMs) and their application in AI-driven solutions including inferencing embedding and knowledge base integration (RAG) for improved data retrieval and contextualization
- Deep knowledge of LLM inference optimization techniques including prompt tuning caching quantization and latency reduction across different model families
- Hands-on experience with building or fine-tuning AI agents and deploying models in production environments
- Familiarity with research papers implementing state-of-the-art methods and adapting them to practical applications
- Published research in the field of Machine Learning AI or Computer Vision
Employment Type
Full Time
Key Skills
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