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Apple Senior / Staff Machine Learning Engineer Apple ML Data Platform United States, West Virginia 199566851
Yesterday
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You’ll have the opportunity to work on 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.
- As a member of the Apple ML Data Platform team, your responsibilities will include:
- Prototype and optimize GenAI models, including open-source models, for scalable production use
- 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
- Expertise in building and running large scale distributed systems.
- 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
- Experience in the below is preferred:
- 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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