This role pays more than
57%
of similar roles. Most pay
$187,850–$254,750
— the shaded band above.
At the midpoint, this role pays about
$231k
versus about
$221k
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
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
As an Applied Machine Learning Engineer, Platform Architecture, you will join the SoC Architecture team to build ML and generative AI systems that inform how future System-on-Chip designs are architected and tuned. You will design and build advanced workflows to automate workload analysis and architectural exploration while applying deep learning and generative AI techniques to large-scale time-series telemetry data. Your daily work involves translating these insights into concrete hardware and software changes to improve performance, power, and performance per watt across fabric, memory subsystems, and power management policies. You will collaborate with silicon and OS teams to implement and validate these improvements on real silicon. The role requires proficiency in Python, modern deep learning frameworks, and experience with large-scale data, while addressing the complex performance-power tradeoff space inherent in modern SoC designs.
What does a Machine Learning Engineer earn in California?
Median $246394 from 172 postings across 28 companies.
Design and build advanced ML and generative AI workflows to automate workload analysis and SoC architectural exploration.
Apply deep learning and generative AI techniques to large-scale time-series telemetry data.
Identify hardware and software improvements based on insights from machine learning research.
Translate technical findings into concrete changes to improve performance, power, and performance per watt.
Partner with silicon and OS teams to implement architectural changes on real hardware.
Validate and oversee the integration of these changes through the full product lifecycle to final shipment.
What we're looking for
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Experience deploying complex ML systems in production.
Experience applying modern ML techniques to large real-world datasets.
Programming experience in Python and modern deep learning frameworks.
Knowledge of SoC compute, memory, and power-management subsystems (preferred).
Depth in time-series analysis and feature engineering on streaming telemetry (preferred).
Experience applying ML for decision driving, policy optimization, and searching large configuration spaces (preferred).
Track record of training large-scale models across distributed clusters; building agentic frameworks; or 10+ years experience with an advanced degree (preferred).
Machine Learning
C++
Python
PyTorch
GPU
CPU
Neural Engine
SoC Architecture
Compiler
Simulation
System Architecture
Production Inference
Training Environments