Senior Machine Learning Engineer - Large Language Model (LLM) Development and Optimization

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; and 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!

Minimum Qualifications:

• 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.

Preferred Qualifications:

• 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.

At Apple, 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 $181,100 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's 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 at Apple, reimbursement for certain educational expenses including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.

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.