Applied Sensing & Health Algorithm Engineer at Apple

San Diego, California, United States -

Full Time

Start Date

Immediate

Expiry Date

04 May, 26

Salary

0.0

Posted On

03 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Signal Processing, Biomechanics, Machine Learning, Controls, Dynamics, Statistics, Programming, Python, Spark, Modeling, Data Pipelining, On-Device Implementation, Generative AI, Interpersonal Skills, Communication, Privacy-Preserving ML

Industry

Computers and Electronics Manufacturing

Description

The Applied Sensing & Health team has built innovative ways for users to improve their health, watch for their lives, and get personalized insights from their daily patterns through multimodal sensing and AI models. This team combines advanced machine learning, including integration, adaptation, and tuning of foundation models, with contextual sensing, bolstered by innovative study design, to derive user insights spanning health, fitness, and safety. This has enabled us to deliver meaningful features like Cardio Fitness, Journaling Suggestions, Fall and Crash Detection, and our latest advances to bring our suite of Fitness metrics to AirPods Pro 3, delivering 50 workout types in a single year. DESCRIPTION Most importantly, you will help ship interactive features that impact millions of users on a daily basis. You take responsibility; you demonstrate creativity, initiative, and the ability to work to deadlines. You feel a personal stake in the product you ship. You thrive in uncertainty and strive to bring order to it. You keep your eye on the ball; you build strong relationships; and you are constantly looking to improve yourself and your team. MINIMUM QUALIFICATIONS PhD or 5+ years research experience in Mechanical Engineering, Biomedical Engineering, Electrical Engineering / Computer Science or related field with relevant domain knowledge Experience in some of the following: signal processing, biomechanics, machine learning, controls, dynamics, statistics, programming Experience applying a scientific approach to machine learning modeling from defining hypotheses, designing experiments, testing, failure analysis, and guiding data collection in user studies Strong working knowledge of Python, Spark, or equivalent and running experiments with data at scale PREFERRED QUALIFICATIONS Hybrid scientist/engineer who can do modeling, data pipelining, and/or on-device implementation Experience developing generative AI systems, such as large language models, in an applied setting, including post-training techniques like supervised fine-tuning, adapter training, and reinforcement from human feedback Excellent interpersonal skills and communication (written and verbal) Experience working with cross-functional and/or interdisciplinary teams Familiarity with privacy-preserving ML techniques is a plus

Responsibilities

You will help ship interactive features that impact millions of users daily. You will take responsibility, demonstrate creativity, and work to deadlines.