On-Device Machine Learning Engineer

Apple Inc

Quick summary

Work type: On-site
Location: Sunnyvale, CA
Salary: $181,100–$318,400 / yr
Posted: 56 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $221k

This role $250k

$154k most similar roles pay here $336k

This role pays more than 81% of similar roles. Most pay $193,000–$249,750 — the shaded band above. At the midpoint, this role pays about $250k versus about $221k for comparable roles.

Based on 239 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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · On-Device Machine Learning Engineer

Apply Now Log in to save

Join our Video Computer Vision team as a Machine Learning Integration Engineer, where you will play a pivotal role in deploying advanced vision models on Apple devices. You’ll work closely with hardware and software teams to optimize the performance, efficiency, and scalability of these models, ensuring they meet stringent power consumption requirements while delivering cutting-edge user experiences. Your daily tasks include converting and integrating foundation models for on-device deployment, evaluating their performance, and refining inference latency. Ideal candidates possess a strong grasp of model compression techniques like pruning and quantization, alongside extensive experience in Python and C++, and familiarity with PyTorch and the machine learning development lifecycle. Knowledge of CoreFoundation, RealityKit, and CoreML frameworks is a plus, as well as an understanding of real-time video pipelines and Swift programming.

Skills

Python C++ PyTorch CoreML Swift CoreFoundation RealityKit MultiModal LLMs model compression techniques pruning distillation quantization weight clustering data preprocessing model training evaluation deployment

What you'll do

Convert and integrate foundation models for deployment on Apple devices.
Evaluate power consumption and performance of ML models on Apple hardware.
Optimize inference latency and efficiency of CV/ML models for on-device use.
Develop innovative techniques to enhance model performance, efficiency, and scalability.
Work with teams across HW, SW, and AI to integrate ML components into production systems.

What we're looking for

Strong knowledge of model compression techniques (pruning, distillation, quantization).
Solid understanding of operating systems and extensive programming in Python and C++.
Experience working with PyTorch for machine learning model development.
Foundational understanding of multimodal large language models and ML integration.
Ability to evaluate power and performance of CV/ML models on Apple devices.

Similar roles

Sr Engineer, Machine Learning (On-device Learning SW)

Qualcomm

San Diego, CA 45 days ago $140,800–$211,200

Python C/C++ PyTorch Qualcomm QNN SDK Android programming Neural network model training Neural network model quantization Docker CI/CD Git Linux CUDA OpenCL

Save

Staff Machine Learning Engineer – On-Device AI/ML

Qualcomm

Santa Clara, CA +1 60 days ago $160,500–$240,700

Python C++ Android Linux Windows Git CI/CD Docker Kubernetes AWS GCP Azure Terraform Prometheus PostgreSQL ONNX PyTorch LiteRT ONNXRuntime QualcommAIEngineDirectSDK

Save