HID Algorithms Manager

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At Apple, novel algorithms quickly have a way of becoming extraordinary products, services, and customer experiences. Bring passion and dedication to your job and there's no telling what you could accomplish. This is your opportunity to be part of a world class research and engineering team building the next-generation of advanced algorithms for sensing technologies in iPhone, iPad, Pencil, Watch and more. Our group has diverse backgrounds in machine learning, signal and image processing, statistics, estimation theory, control, physics and human factors. We are looking for a manager to lead a small group of hardworking engineers and work with cross-disciplinary teams across the company over the full product cycle. You will be responsible for developing innovative solutions to challenging technical problems and delivering key product features on time and with high quality. To lead the team effectively, you will draw deeply on your technical expertise. To represent the team well, you will need sufficient engineering breadth to have productive conversations with firmware and software teams, hardware technology teams, mechanical engineers, designers, and many other specialists across Apple. Knowledge of machine learning, signal processing, probabilistic modeling, statistics and embedded programming will increase your effectiveness in this position.
We are looking for candidates who have experience in technical leadership or management of a small team for several years. We would like to hear specific, detailed examples of ways you have broken complex problems into manageable pieces. We would love to learn about projects where you have combined disparate skills to develop and ship a product. A strong candidate will be able to communicate complex topics to people from a variety of backgrounds and technical abilities and adapt their speech and writing to different audiences.
  • BS and a minimum of 10 years relevant industry experience.
  • Experience in algorithm development for classification, filtering, noise modeling, signal processing or control.
  • Ph.D. with 2 years of industry experience (or M.S. with 5 years) EE, CS, Statistics, Mathematics, Physics, or another engineering or technical field.
  • At least 4 years managing an engineering team.
  • Strong theoretical knowledge of fundamental concepts such as linear algebra, random processes and statistics.
  • Knowledge of deep learning and classical machine learning techniques.
  • Experience with embedded or resource-constrained systems.
  • Excellent communication, presentation, and documentation skills.
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,000 and $313,000, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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. Learn more about your EEO rights as an applicant.

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