Job Description

Locations

• Cupertino, California, United States 95014

Salary

Salary not disclosed

Skills Required

• synthetic training data generationintermediate
• model performance optimizationintermediate
• agentic workflows designintermediate
• RAG systems implementationintermediate
• tool calling optimizationintermediate
• reasoning tasks optimizationintermediate
• LLM researchintermediate
• NLP researchintermediate
• agentic systems researchintermediate
• translating research insights into solutionsintermediate
• collaboration with multidisciplinary teamsintermediate
• AI integration into user experienceintermediate

Required Qualifications

• Advanced degree (MSc/PhD) in Machine Learning, Computer Science, or a related quantitative field; or BSc with 2+ years of relevant industry experience (experience, 2 years)
• Hands on experience in machine learning engineering outside of research (experience)
• Strong Python proficiency, including development, debugging, and design, coupled with extensive experience using ML frameworks (e.g. PyTorch, Jax, HuggingFace) (experience)
• Excellent problem-solving, critical thinking, and interpersonal skills, with a collaborative attitude (experience)

Preferred Qualifications

• 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 (experience)
• Applying LLMs for synthetic data generation (e.g. for knowledge distillation) or applying reinforcement learning for post-training or fine-tuning of LLMs. (experience)
• 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)
• Experience with training, fine-tuning, and deploying LLMs in production environments. (experience)
• Proficiency in evaluating LLMs for specific product tasks and performance metrics. (experience)

Responsibilities

• 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.

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