Machine Learning Research Engineer - Large Language Models (LLMs), Siri Planner Team

Join the Siri Planner team as a Machine Learning Research Engineer and play a pivotal role in shaping the future of virtual assistants. You’ll contribute to revolutionizing how millions of Siri users worldwide interact with their devices by building ground breaking AI solutions.

As a Machine Learning Research Engineer, you will help with initiatives to significantly advance Siri’s natural language understanding and planning capabilities using innovative LLM technologies. YOUR CORE RESPONSIBILITIES WILL INCLUDE:

• 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.

• 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

• 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.

Base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.

Employees also have the opportunity to become a shareholder through participation in discretionary employee stock programs. Employees are eligible for discretionary restricted stock unit awards, and can purchase stock at a discount if voluntarily participating in the Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Benefits.

Note: Benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

We are an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.