Machine Learning Engineer – Computer Vision & Data Systems

At Apple, we are dedicated to creating technologies that enrich people's lives.

Our teams develop products and experiences that empower millions of users

globally, by combining world-class engineering with a deep commitment to

innovation, quality, and privacy. We are seeking a Machine Learning Engineer

with strong expertise in computer vision and large-scale data processing. In

this role, you will contribute to the development of next-generation real-time

sensing and data intelligence systems by designing algorithms, building scalable

data pipelines, and collaborating with multi-functional teams to deliver

high-impact, production-quality solutions.

DESCRIPTION

As a Machine Learning Engineer, you will: - Design, build, and maintain

large-scale data processing workflows, ensuring efficiency, scalability, and

reliability across diverse data sources and modalities. - Develop and optimize

computer vision models that power core product experiences, including areas such

as image understanding, multi-view geometry, 3D reconstruction, and visual

recognition. - Partner closely with engineering, research, and data teams to

translate product requirements into technical solutions. This includes

prototyping models, running large-scale experiments, improving data quality, and

ensuring seamless integration of algorithms into production systems. - Explore

emerging areas such as LLM-based agents, retrieval-augmented systems, and

tool-oriented reasoning to improve internal workflows or data operations.

MINIMUM QUALIFICATIONS

Strong foundation in computer vision, including experience with deep

learning–based vision models and at least one area such as detection,

segmentation, 3D vision, geometric methods, tracking, or self-supervised

learning. Hands-on experience developing machine learning models using

frameworks such as PyTorch or TensorFlow. Experience building or optimizing

large-scale data pipelines (e.g., distributed ETL, dataset generation,

annotation workflows, data validation, or high-throughput processing).

Proficiency in Python or C++ for algorithm development and data processing.

Experience working with distributed computing frameworks (e.g., Spark, Ray, or

equivalent).

PREFERRED QUALIFICATIONS

PhD in a relevant field with research directly related to computer vision,

large-scale data systems, or multimodal learning. Experience designing or

evaluating agentic systems, including LLM-powered tools, RAG pipelines, or

automated data reasoning workflows. Familiarity with prompt engineering,

tool-use patterns, and LLM model behavior. Experience deploying ML models at

scale, including monitoring, evaluation, and continuous improvement. Knowledge

of data quality assessment, dataset curation methodologies, and evaluation

frameworks. Experience with GPU-based optimization, large-batch training, or

distributed training. Strong multi-functional collaboration skills and the

ability to lead technical initiatives.