AIML - Senior Machine Learning Engineer, Audio Generation, Siri and Information Intelligence

Cupertino, California, United States
Machine Learning and AI

Summary

Posted:
Role Number:200584647
As part of Apple Intelligence, Siri team is at the forefront of the next revolution in machine learning and NLP. Our innovative product redefines computing by leveraging cutting-edge technologies in audio generation, multimodal FM, and Conversational AI. We are dedicated to creating groundbreaking conversational assistant technologies for both large-scale systems and new devices, building upon our legacy of intelligent assistant solutions that already assist millions of users worldwide. We are seeking a high caliber Senior Machine Learning Engineer to join our dynamic team. The ideal candidate will play a pivotal role in the evaluation and enhancement of our Apple Intelligence products. They will collaborate closely with cross-functional teams to define innovative approaches using audio generation and multimodal FM to evaluate state-of-the-art Apple Intelligence products and models. They will work with large amounts of real-world data to analyze and propose changes to the Siri user experience. This role offers an exciting opportunity to contribute to the advancement of AI systems and shape the future of Artificial Intelligence.

Description

As Siri is becoming increasingly complex AI system, it is critical to understand the impact of each ML model on other dependent models, while assessing the impact on Siri end-user experience. Siri team owns the development of advanced evaluation methodologies for ML based systems, model interpretability, and experimentation, to ensure that every release delivers an improved Siri user experience. You will join a team that is redefining computing, creating groundbreaking conversational assistant technologies for both large scale systems and new client devices, and with the people who built the intelligent assistants. The team is searching for talented ML Engineers to work with a passionate, product-focused team to define new approaches for evaluating ML based systems, conversational AI, and model interpretability You will run experiments, statistically interpret data with a mind on causation, data visualization, plus designing, building, and evaluating models. You will work with large amounts of real-world data to analyze and propose changes to Siri user experience. You will ensure data quality throughout all stages of acquisition and processing, data wrangling, etc. Your expertise in defining and measuring the online and offline end-to-end metrics will help communicate, evaluate, and iterate on state-of-the-art deployed models and predictors.

Minimum Qualifications

  • Knowledge in multimodal foundation models
  • Extensive experience with machine learning frameworks like Tensorflow, PyTorch and Python
  • Good experience with large-scale data processing and distributed systems
  • Excellent problem solving, critical thinking, and communication skills.
  • Excellent data analytical skills.
  • Proven track record to dive into data to discover hidden patterns and conduct error/deviation analysis

Key Qualifications

Preferred Qualifications

  • Expertise in any of the following areas is a BIG plus: foundation Models, LLMs, Audio generation , adversarial machine learning, conversational dialogue systems, natural language generation, and question-answering.
  • Exposure to model interpretability techniques and their real-world advantages/drawbacks
  • Strong attention to detail.
  • B.S., M.S. or Ph.D. in Computer Science, Electrical Engineering or related field is preferred

Education & Experience

Additional Requirements

Pay & Benefits

  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.