AIML - Machine Learning Engineer, Siri Conversation Intelligence
3 months ago
The Siri Conversation Intelligence (SCI) team is creating groundbreaking technology for large scale systems, spoken language, machine learning, and LLMs to enable better conversational experience with Siri. The features we create are redefining how hundreds of millions of people use their computers and mobile devices to fulfill their requirements and find what they are looking for. As part of the SCI team, you will work with the talent dense team who crafted the intelligent assistant that helps users get things done — just by asking. You will be responsible for doing research in the deep learning field and developing the most advanced natural language and conversation understanding systems. You should be passionate about working with software and platform engineers to integrate the models on-device and improve natural language understanding ability of Siri. Excellent interpersonal skills will be required to coordinate work across multiple teams to ship the state-of-the-art technology to production and impact all Siri users.
Description
As a member of this team, the successful candidate will:
- Develop novel ML/DL models including LLMs for natural language and conversational understanding.
- Work with software and platform engineers to convert and compile the models to run on device and integrate them with runtime systems.
- Optimize latency and performance of the models.
- Diagnose model errors and perform accuracy hill climbing for shipped products.
Minimum Qualifications
- Solid understanding of state-of-the-art technology in machine learning, deep learning (including LLMs) and natural language understanding.
- Excellent problem-solving (e.g. via building forward-looking prototype systems), critical thinking, strong communication, and collaboration skills.
Preferred Qualifications
- 3-5+ years proven programming skills using standard ML tools such as C/C++, Python, PyTorch, Tensorflow, Hugging Face, etc.
- Hands-on experience working (training, fine-tuning, optimizing, deploying) with large models (e.g. LLMs).
- Hands-on experience applying common machine learning optimization techniques, like quantization and distillation, to reduce the resource consumption and/or eliminate latency.
- Publication at top ML/DL/NLP conferences such as NeurIPS, ACL, EMNLP, etc. is a plus.
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.
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