AIML - Machine Learning Engineer - Computer Vision & Audio, MIND

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 13, 2026

Salary

$140K-$258K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

71% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

AIML - Machine Learning Engineer - Computer Vision & Audio, MIND Seattle, United States of America The Machine Intelligence, Neural Design (MIND) team, part of Apple's AIML organization, is leading Apple-wide innovation on HW/SW co-design for efficient inference. With roots in ML, computer vision, and energy efficiency research, our team is strategically positioned to contribute to diverse initiatives ranging from shipping features in well-known Apple products to ambitious, long-term research projects. We are seeking a hands-on Machine Learning Engineer to drive the data & evaluation lifecycle for our production models. In this role, you will focus on designing and scaling high-performance data processing pipelines, ensuring data quality, performing in-depth failure analysis on production models, and implementing advanced data augmentation techniques to boost model performance. This includes but is not limited to crafting creative techniques to analyze audio & video datasets, designing metrics to understand user behavior & evaluate performance of machine learning models. You will innovate across the entire end-to-end ML production pipeline, bridging the gap between hardware, software, and modeling, ensuring our ML systems are robust, efficient, and scalable. We are seeking a Machine Learning Engineer to design and deliver innovative features and models that advance our ML systems. In this role, you will scale model evaluation workflows, build robust data pipelines, and optimize performance across the stack. Your responsibilities will include: * Pipeline Scaling & Optimization: Design, build, and maintain scalable ETL/ELT data pipelines using tools like Spark, & Airflow to handle large-scale datasets. Optimize existing pipelines for

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