Apple · 3 months ago
Machine Learning Research Engineer - Large Language Models (LLMs), Siri Core Modeling
Cupertino, California, United States
Full-time
Onsite
Entry, Mid Level
$147K/yr - $272K/yr
2+ years expApple is seeking a Machine Learning Research Engineer to join the Siri Planner team and shape the future of virtual assistants. The role involves developing innovative AI solutions to enhance Siri's natural language understanding and planning capabilities using advanced LLM technologies.
AppsArtificial Intelligence (AI)BroadcastingDigital EntertainmentFoundational AIMedia and EntertainmentMobile DevicesOperating SystemsTVWearables
Responsibilities
Developing innovative systems for synthetic training data generation and implementing strategies for the continuous optimization of model performance
Designing and implementing agentic workflows and RAG systems to enhance Siri’s capabilities
Optimizing model performance for tool calling and reasoning tasks
Actively staying at the forefront of academic and industry research in LLMs, NLP, and agentic systems, and translating novel insights into practical solutions
Collaborating closely with a multidisciplinary team of researchers, software engineers, and product designers to seamlessly integrate AI innovations into the Siri user experience
Qualification
Required
Advanced degree (MSc/PhD) in Machine Learning, Computer Science, or a related quantitative field; or BSc with 2+ years of relevant industry experience
Hands on experience in machine learning engineering outside of research
Strong Python proficiency, including development, debugging, and design, coupled with extensive experience using ML frameworks (e.g. PyTorch, Jax, HuggingFace)
Excellent problem-solving, critical thinking, and interpersonal skills, with a collaborative attitude
Preferred
Proven hands-on experience in machine learning engineering for large-scale models, with a strong focus on generative AI, LLMs, Retrieval Augmented Generation (RAG), or agentic systems
Applying LLMs for synthetic data generation (e.g. for knowledge distillation) or applying reinforcement learning for post-training or fine-tuning of LLMs
A successful track record of building and deploying end-to-end ML data pipelines (data preparation, storage, training, and inference) in cloud or on-premise environments
Experience with training, fine-tuning, and deploying LLMs in production environments
Proficiency in evaluating LLMs for specific product tasks and performance metrics
Benefits
Comprehensive medical and dental coverage
Retirement benefits
A range of discounted products and free services
Reimbursement for certain educational expenses — including tuition
Discretionary bonuses or commission payments
Relocation
Company
Apple
Apple is a technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10001+ employees
H1B Sponsorship
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Funding
Current Stage
Public CompanyTotal Funding
$5.67BKey Investors
Berkshire HathawayMicrosoftSequoia Capital
2025-05-05Post Ipo Debt· $4.5B
2025-01-16Post Ipo Debt· $0.31M
2021-04-30Post Ipo Equity
Leadership Team
Tim Cook
CEO
Craig Federighi
SVP, Software Engineering
Recent News
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