Job Description
Summary
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
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
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