below marketmost similar roles pay hereabove market
This role pays more than
54%
of similar roles. Most pay
$199,725–$254,750
— the blue band above.
At the midpoint, this role pays about
$231k
versus about
$227k
for comparable roles.
Based on 240 similar postings.
Employer
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
3499 open roles
on FindRole.
Listed pay typically runs
$166,600–$277,600
across 2707 roles with salary data.
The Senior Machine Learning Engineer - ML Platform joins the Apple Ads Machine Learning Platform team to design and develop secure, scalable back-end systems. This role involves building world-class platform capabilities that enable various ads teams to improve and scale machine learning features, models, and applications. Key responsibilities include developing ML infrastructure, frameworks, services, SDKs, APIs, and automation UIs while managing the full machine learning lifecycle, including training, evaluation, deployment, and serving. The candidate must utilize technologies such as PyTorch or TensorFlow to address challenges in advertising, recommender systems, and information retrieval. The work focuses on building high-performing systems that support continuous experimentation and large-scale model optimization, specifically addressing the technical requirements of privacy-preserving machine learning and low-latency serving for diverse model types like LLMs.
What does a Machine Learning Engineer earn in New York?
Median $231150 from 51 postings across 20 companies.
Design and develop secure, scalable back-end systems for machine learning platform capabilities.
Build and maintain ML infrastructure, frameworks, and services used by multiple internal teams.
Develop SDKs, APIs, and automation UIs to improve the developer experience for ML practitioners.
Implement automation and CI/CD pipelines for production machine learning systems.
Manage the full ML lifecycle including training, evaluation, deployment, and serving/inferencing.
Optimize large-scale models for low-latency serving and distributed training.
Build and operationalize foundation models, LLMs, and privacy-preserving ML solutions.
Perform performance tuning and debugging for mission-critical production code.
What we're looking for
Experience writing mission-critical code for production machine learning systems.
Experience building ML infrastructure, frameworks, or services used by multiple teams.
Experience building SDKs, APIs, and automation UIs for development teams.
Proven experience building automation and CI/CD.
Solid understanding of the ML lifecycle, including training, evaluation, deployment, and serving/inferencing.
Working knowledge of deep learning architectures and training frameworks such as PyTorch or TensorFlow.
Prior experience applying ML at scale in advertising, recommender systems, or information retrieval.
PhD in Computer Science with 3+ years of engineering and 5+ years of ML experience; MS with 6+ years engineering and 5+ years ML; or BS with 7+ years engineering and 5+ years ML.
PyTorch
TensorFlow
CI/CD
LLMs
Distributed Training
Deep Learning
Machine Learning
API
SDKs
Reinforcement Learning
Multimodal Models
Data Drift
Privacy-Preserving ML
Agentic AI
PyTorch
TensorFlow
Machine Learning
Deep Learning
CI/CD
Data Pipelines
Feature Stores
Workflow Orchestration
LLM
Streaming
Information Retrieval
Recommender Systems
Data Modeling