Senior HID Algorithms Engineer

San Diego, California, United States


Role Number:200289505
Join the innovative engineering team that uses sensor signal processing to produce the next generation of human interfaces for iPhone, iPad, Mac, Apple Watch, and exciting new products. Our team comes from diverse backgrounds, including signal and image processing, statistics, machine learning, controls, physics, firmware and software development, neuroscience, and human factors. We are looking for a hardworking algorithms engineer who works well in cross-disciplinary teams over a full product cycle. HID operates at the intersection of hardware, software, and design. This means that the wide variety of problems you will solve have many interesting facets and you will get to work with specialists from all across Apple.

Key Qualifications

  • Processing and analyzing complex data using statistics, probability theory and linear algebra concepts
  • Algorithm design and development for classification, filtering and signal processing
  • Training, evaluating and exploring different machine learning model architectures
  • Prototyping in Python, MATLAB, or a similar high-level language
  • Experience using one or more machine learning frameworks such as scikit-learn, PyTorch, TensorFlow or Keras
  • Excellent communication, presentation, and documentation skills


We are looking for an algorithm design specialist with experience developing Machine Learning based algorithms. 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. As a Senior HID algorithm engineer you will combine skills from a variety of fields to solve complex data processing and sensing challenges. 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. You should have excellent mathematical skills and experience working with algorithms and data, be proficient at programming, and have a desire to work closely with others in a multi-functional team. In return, you will get to work on challenging and fascinating problems with hardworking co-workers, and ship great solutions at scale.

Education & Experience

M.S. or PhD in EE, CS, Statistics, Mathematics, or another engineering or technical field Apple’s most important resource, our soul, is our people. Apple benefits help further the well-being of our employees and their families in meaningful ways. No matter where you work at Apple, you can take advantage of our health and wellness resources and time-away programs. We’re proud to provide stock grants to employees at all levels of the company, and we also give employees the option to buy Apple stock at a discount — both offer everyone at Apple the chance to share in the company’s success. You’ll discover many more benefits of working at Apple, such as programs that match your charitable contributions, reimburse you for continuing your education and give you special employee pricing on Apple products. Apple benefits programs vary by country and are subject to eligibility requirements. 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. Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Apple is a drug-free workplace.

Additional Requirements

  • - Working with embedded or resource-constrained systems, and with C or C++
  • - 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.