Display Algorithm Engineer
Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 12, 2026. Apple scores B on the Alion truth index.
Apple is looking for a Display Algorithm Engineer to drive the development of advanced display technologies. This role focuses on innovative display algorithms and machine learning models that optimize and enhance Apple display products across all platforms. We want for someone passionate about analyzing engineering problems with data and delivering algorithms that achieve optimal performance.
Description
As a member of the Display Algorithm team, you will collaborate with teams across Apple that are building the most advanced display products in the world. You will develop algorithms grounded in machine learning models and large-scale data analysis, starting early in a product's lifecycle to identify potential challenges and their solutions. You will translate cross-functional insights and data into algorithms and models ready for implementation.
Minimum Qualifications
M.S. in Electrical Engineering, Computer Science, Optics, Physics, or a related quantitative field with 3+ years of industry experience (or equivalent practical experience)
Proficiency in Python and fundamental machine learning concepts, with hands-on experience using frameworks such as PyTorch, TensorFlow/JAX, or Scikit-learn
Experience with the ML lifecycle: data curation/cleaning, model exploration, training/fine-tuning, and systematic evaluation
Working knowledge of digital image processing, and computer vision techniques
Preferred Qualifications
Ph.D. in Electrical Engineering, Optics, Physics, or Computer Engineering with expertise in image processing and machine learning
Experience with multimodal machine learning (e.g., VLM), including adapting or fine-tuning large pre-trained multimodal models for domain-specific or scientific imagery
Strong domain background in display technologies (e.g., OLED, LCD), display systems and driving, optical metrology/calibration, or color science
Track record of bridging physical/hardware domain knowledge with data-driven ML models
First-author publication record in peer-reviewed ML or engineering venues (e.g., NeurIPS, ICML, ICLR, CVPR, IEEE, or equivalent)
Excellent cross-functional communication and collaboration skills to drive technical solutions across hardware, software, and display engineering teams