Sr. Machine Learning Engineer, Siri Speech

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$181,100–$318,400 / yr
Posted
28 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $221k
This role $250k
$165k most similar roles pay here $335k

This role pays more than 79% of similar roles. Most pay $192,525–$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 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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At a glance

TL;DR · Sr. Machine Learning Engineer, Siri Speech

As a Senior Machine Learning Engineer on the Siri Speech team at Apple, you will play a pivotal role in advancing conversational AI by designing and deploying cutting-edge machine learning models. Your day-to-day responsibilities include building scalable ML pipelines for data ingestion, feature engineering, training, evaluation, and serving, while collaborating with data scientists to transform research prototypes into robust production systems. You will also monitor deployed models for performance degradation and optimize them for efficiency in latency and resource usage. The team focuses on addressing real-world challenges at scale while preserving user privacy, making use of technologies such as PyTorch, TensorFlow, JAX, AWS, GCP, Azure, Docker, Kubernetes, MLflow, Weights & Biases, and Kubeflow to ensure the models are reliable and efficient in a large-scale production environment.

What you'll do

  • Design and train machine learning models for production use cases.
  • Build and maintain scalable ML pipelines from data ingestion to model serving.
  • Monitor deployed models for performance degradation and data drift issues.
  • Optimize models for latency, throughput, and resource efficiency in production.
  • Contribute to the development of ML infrastructure, tooling, and best practices.

What we're looking for

  • Master’s degree in Computer Science, Machine Learning, Statistics, or related field.
  • Proven experience designing and deploying machine learning models in production environments.
  • Expertise in Python and major ML frameworks like PyTorch, TensorFlow, JAX.
  • Experience managing the full lifecycle of machine learning projects from data to deployment.
  • Knowledge of distributed training techniques and large-scale data pipeline management.
  • Strong background in software engineering practices including testing and version control.

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