Apple is looking for a Display Algorithm Engineer to own the development of advanced display activities. This position will focus on innovative display algorithm and machine learning models to optimize and enhance Apple display products across all platforms. Looking for someone passionate to analyze engineering problems using data and will deliver algorithm for optimal performance.

Description

As a member of the Display Algorithm team, you will collaborate with teams across Apple, who are building the state-of-art Display products in the world. You will work on algorithms based on machine learning models and large-scale data analysis. The exploration starts early in a product’s lifecycle to identify possible challenges and their potential solutions. The solution develops rapidly by translating multi-functional insights and data into building algorithms/models for implementation.- Investigate up-to-date Display technologies and generate new approaches, to calibration and rigorous plans to further improve display optical performances.- Develop identification / classification models, image processing for defect inspection to quantify display front of screen performance- Collaborate with diverse and multi-disciplinary teams from display module, manufacturing, test and system team and provide strong leadership and expertise for initiating new project solutions- This individual will serve as a focal point to analyze data between Display Module Team and AIML team delivering ML models necessary to understand, optimize and solve display related problems- Understand display failures, capture appropriate datasets, use appropriate ML libraries and design machine learning experiments to solve the problem

Minimum Qualifications

  • M.S. in EE in Optics, Physics or Computer Engineering, with 3+ years industry experience
  • Experience developing machine learning models in Python, using frameworks and libraries, such as PyTorch, TensorFlow/JAX, Scikit-learn or equivalent

Key Qualifications

Preferred Qualifications

  • Ph. D. in EE, Optics, Physics, Computer Engineering with expertise in Image Processing, Machine Learning
  • Understanding of OLED and LED displays, optical fundamentals, display system and driving
  • First author publication in ML or engineering conferences (like. ICML, ICLR, NeuraIPS, IEEE or equivalent)
  • Excellent communication and leadership skills to work with multi-functional teams

Education & Experience

Additional Requirements

Pay & Benefits

  • 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 $143,100 and $264,200, 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.