Jobs / App***
Machine Learning Research Scientist - Health AIML
App*** · Seattle, WA, United States
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Seattle, WA, United States171,600-302,200 USD/yearlyOnsite
Remuneration
171,600-302,200 USD/yearly
Location
Seattle, WA, United States
Visa sponsorship
Sponsors visa
Job summary
The Health AIML team is at the forefront of machine learning and health science at App***. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impact millions of users.
Benefits
At Apple, base pay is one part of our total compensation package and is determinThis provides the opportunity to progress as you grow and develop within a role.The base pay range for this role is between $171,600 and $302,200, and your baseIncluding: Comprehensive medical and dental coverage, retirementAdditionally, this role might be eligible for discretionary bonuses or commissioLearn more about AppleNote: Apple benefit, compensation and employee stock programs are subject to eli
Qualifications
- Experience in training and evaluating multimodal models.
- Understand of time-series modeling, self-supervised learning, and cross-modal training.
- Ability to thoroughly evaluate and improve deep learning architectures in a self-directed fashion.
- Motivated by safely deploying LLMs in the health and fitness space.
- Minimum
- PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field.
- Industry work experience.
- Experience landing contributions to major LLM training runs.
- Proven track record of publishing SOTA.
- Strong
- experience, and location.
- App*** employees also have the opportunity to become an App*** shareholder through participation in App***'s discretionary employee stock programs.
Responsibilities
- Lead research into health and fitness representation models and multimodal models.
- Design, prototype and scale up new architectures to improve model intelligence.
- Execute and analyze experiments autonomously and collaboratively.
- Study, debug, and optimize model performance and computational performance.
- Contribute to training and inference infrastructure.
- Guide technical and architectural decision.
- Preferred
Degrees
AssociatePhD
Industry
AutomotiveEducation
Company size
Smb
Relocation
Yes