Senior Machine Learning Engineer - Large Language Model (LLM) Development and Optimization
Join Apple’s Software Engineering team, where we push the boundaries of innovation to
enhance every Apple product while safeguarding user privacy and data. We are seeking a
seasoned machine learning researcher with expertise in fine-tuning large language models
(LLMs), optimizing training and inference pipelines, and generating high-quality data to advance
state-of-the-art conversational AI. As part of the Siri Planner team, you’ll have the unique
opportunity to revolutionize the experience for hundreds of millions of Siri users worldwide.
As a Senior Machine Learning Engineer, your mission will be to lead efforts in advancing
Siri’s language understanding capabilities using cutting-edge LLM technologies.
Your responsibilities will include:
• Designing and implementing strategies for fine-tuning and adapting foundation models
for Siri's diverse use cases.
• Developing efficient workflows for generating and curating large-scale datasets to train
robust, domain-specific language models.
• Optimizing training pipelines to reduce resource utilization while maintaining or
improving model performance.
• Collaborating with multidisciplinary teams of researchers, software engineers, and
product designers to integrate AI innovations into Siri's user experience.
• Staying at the forefront of research in LLMs, NLP, and AI, and translating breakthroughs
into actionable improvements.
If you’re passionate about pushing the limits of conversational AI and want to see your work
impact millions of users globally, we’d love to hear from you!
- MSc or PhD in Computer Science, Machine Learning, or a related field. Equivalent
- industry experience will also be considered.
- Published research or significant contributions in the fields of LLMs, NLP, or AI is highly
- desirable.
- Deep expertise in LLM fine-tuning and training: Experience with adapting and
- optimizing large-scale language models such as GPT or BERT for specific tasks and
- domains. Familiarity with model training optimization such as distributed training, low-
- precision techniques, quantization.
- Data generation and augmentation: Knowledge of synthetic data generation, active
- learning strategies, and building robust datasets for model training.
- Strong proficiency in Python and relevant ML frameworks (e.g., PyTorch,
- HuggingFace).
- Solid understanding of evaluation metrics for NLP tasks and experience in benchmarking
- and optimizing model performance.
- Proven ability to design scalable ML pipelines, including pre-processing, training, and
- deployment in production environments.
- Excellent problem-solving, analytical, and collaborative skills.
Apple is 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.