HID Machine Learning Engineer

Zurich, Zurich, Switzerland
Machine Learning and AI

Summary

Posted:
Role Number:200389364
Join the engineering team that turns sensor signals into next-generation human interfaces for AirPods, iPhone, iPad, Macs, and exciting new products. You will be part of a strong team with a wide range of backgrounds, including signal and image processing, statistics, machine learning, human factors, and firmware development. This is a role where you will design and develop high quality efficient data driven algorithm solutions for Apple products.

Key Qualifications

  • Processing and analyzing complex data using statistics, probability theory and linear algebra concepts
  • Algorithm design and development for classification, filtering, noise modeling and/or signal processing
  • Training, evaluating and exploring different machine learning model architectures
  • Building mathematical models and prototyping in Python, MATLAB, or a similar high-level language
  • Experience using one or more machine learning frameworks such as scikit-learn, PyTorch, TensorFlow and Keras
  • Excellent communication, presentation, and documentation skills
  • Additional qualifications desired:
  • Experience with optimization, estimation algorithms, distributed algorithm design, and hands-on implementation of these techniques.
  • Ability to serve as a technical lead — building technical requirements, software design, implementation, and clear communication
  • Experience implementing end-to-end data science and machine learning projects.

Description

We are looking for an algorithm design specialist with experience developing Machine Learning based algorithms. As a HID Machine Learning engineer you will combine skills from a variety of fields to solve complex data processing and sensing challenges. You should have a working knowledge of probabilistic modeling, statistics, and state machines. You must possess strong programming skills in functional and mathematical modeling languages. The process starts early in a product’s lifecycle as we explore what might be possible and identify challenges and their potential solutions, then continues as we rapidly iterate on cleaning and analyzing data, building and testing algorithms, and finishes with detailed implementation, analysis, and validation.

Education & Experience

Ph.D. (or Ms.C) in EE, CS, ME, mathematics, physics, or another engineering or technical field Apple is an equal opportunity employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities.

Additional Requirements