Machine Learning Engineer, Data for Foundation Models

Apple Inc

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Quick summary

Work type: On-site
Location: Seattle, WA
Salary: $142,300–$263,300 / yr
Posted: 13 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $229k

This role $203k

$126k $294k

below market most similar roles pay here above market

This role pays less than 73% of similar roles. Most pay $202,800–$254,750 — the blue band above. At the midpoint, this role pays about $203k versus about $229k for comparable roles.

Based on 240 similar postings.

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer, Data for Foundation Models

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The Machine Learning Engineer, Data for Foundation Models joins the Intelligent System Experiences team to develop core modeling technology for products like Genmoji, Image Playground, and Photos Generative Edits. This role focuses on building high-quality datasets for foundation model training, specifically improving diffusion or auto-regressive models through image and video data. You will design data annotation, enrichment, curation, and synthetic data generation pipelines using classic or genAI tools to improve model quality across specific dimensions. The position requires expertise in ML fundamentals, applied research, and data ablation experiments. Necessary technical skills include proficiency with PyTorch or JAX frameworks and large-scale data frameworks like Hadoop or Ray. You will work on web-scale datasets and distributed training to advance state-of-the-art generative AI technology.

What does a Machine Learning Engineer earn in Washington?

Median $241750 from 69 postings across 15 companies.

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Skills

PyTorch JAX Hadoop Ray Generative AI Synthetic Data Generation Data Annotation Distributed Training Machine Learning Image Generation

What you'll do

Build high-quality datasets for training foundation models.
Construct large-scale and targeted datasets involving image or video content.
Design data annotation, enrichment, curation, and synthetic data generation pipelines.
Improve the quality of diffusion or auto-regressive foundation models.
Conduct data ablation experiments to improve image generation or understanding models.
Implement and optimize model training using PyTorch, JAX, Hadoop, or Ray.
Adopt impactful AI research developments to pioneer proprietary and experimental ideas.

What we're looking for

M.S. or PhD in Computer Science, Electrical Engineering, Robotics, Statistics, Applied Mathematics, or equivalent experience.
3+ years of experience improving modern image generation or image understanding models through data ablation experiments.
Knowledge of ML frameworks such as PyTorch or JAX.
Experience leveraging large-scale data frameworks such as Hadoop or Ray.
Experience working in an academic or industrial research environment.
Excellent communication skills, bias-for-action, and the ability to drive clarity in ambiguous circumstances.
Hands-on experience improving the quality of diffusion image generation models through training data improvements (preferred).
Track record of strong industrial research output, shipped complex projects, or publications at top-tier venues (preferred).