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Apple Staff Machine Learning Engineer Apple ML Data Platform United States, Washington, Seattle 95104740
21.04.2025
You’ll have the opportunity to work on a variety of exciting challenges, from multimodal data models (text, images, audio, and more) to developing cutting-edge generative AI solutions. This includes accelerating data-centric ML, improving model performance through intelligent data workflows, and experimenting with novel approaches like synthetic data generation and automated labeling. Our work spans the entire ML lifecycle, from experimentation to deployment, and you’ll play a key role in shaping how AI models are built, optimized, and scaled.
* Prototype and optimize GenAI models, including open-source models, for scalable production use* Build a platform that enables teams to easily configure models, apply tuning strategies (e.g., LoRA/QLoRA), perform quantization, and get models production-ready for scalable deployment* Continuously improve platform capabilities to handle next-gen ML workloads, including foundation models and retrieval-augmented systems* Use ML techniques to drive smarter data workflows - including synthetic data generation, automated labeling, active learning, and data curation* Collaborate across research and engineering teams to accelerate experimentation* Collaborate closely with teams across the stack to enable high-quality, end-to-end ML experiences* Use and extend tools built on modern ML frameworks* Optimize platform components for large-scale ML workloads across distributed systems* Diagnose, fix, improve, and automate complex issues across the entire stack to ensure maximum uptime and performance
- Strong foundation in machine learning, with hands-on experience across the end-to-end ML workflow - including data preparation, pipeline development, experimentation, evaluation, and deployment
- Familiarity with modern generative techniques (e.g. transformers, diffusion, retrieval-augmented generation)
- Proven experience building and delivering data and machine learning infrastructure in real-world production environments
- Familiarity with fine-tuning workflows, model optimization, and preparing models for scalable inference.
- Familiarity with generative AI and its applications in accelerating and enhancing machine learning workflows
- Experience configuring, deploying and troubleshooting large scale production environments
- Experience in designing, building, and maintaining scalable, highly available systems that prioritize ease of use
- Extensive programming experience in Java, Python or Go
- Strong collaboration and communication (verbal and written) skills
- Comfortable navigating ambiguity and evolving technical landscapes, especially in fast-moving areas
- B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience
- Proficiency in one or more ML frameworks
- Experience with containerization and orchestration technologies, such as Docker and Kubernetes.
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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