Machine Learning (MLOps) Engineer

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$212,000–$318,400 / yr
Posted
43 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $216k
This role $265k
$152k most similar roles pay here $336k

This role pays more than 87% of similar roles. Most pay $182,527–$249,750 — the shaded band above. At the midpoint, this role pays about $265k versus about $216k 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 969 open roles on FindRole.

Listed pay typically runs $163,300–$272,100 across 756 roles with salary data.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · Machine Learning (MLOps) Engineer

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As an MLOps Engineer at our company, you will join a dynamic team responsible for the development and maintenance of robust machine learning infrastructure. Your primary focus will be on designing and implementing scalable ML systems, from data ingestion to model deployment, ensuring continuous improvement through automated pipelines and CI/CD practices. You will work closely with ML Engineers and Data Scientists to establish best practices for model governance and validation, leveraging tools like Ray, MLflow, Kubeflow, and TensorFlow or PyTorch. Additionally, you will utilize AI coding assistants and LLM-based tools to enhance productivity and streamline development processes, while maintaining a strong understanding of cloud platforms and container orchestration technologies such as AWS, Azure, GCP, and Kubernetes. This role demands expertise in distributed systems, databases, and data pipeline orchestration tools like Airflow or Prefect, ensuring that our ML solutions are reliable and efficient at scale.

Skills

AWS Kubernetes Python RFMLflow TensorFlow PyTorch CI/CD GitHub Actions Airflow Prefect Jenkins ArgoCD LLM-based tools Ray SageMaker Vertex AI Docker MLOps

What you'll do

  • Design and implement advanced ML infrastructure frameworks to accelerate model development and delivery.
  • Maintain automated pipelines for training, evaluating, versioning, and deploying models.
  • Champion observability, incident response, and feedback loops for continuous model health.
  • Enforce model governance and validation standards across teams to ensure compliance.
  • Identify and resolve bottlenecks in ML workflows to improve system reliability and performance.

What we're looking for

  • 8+ years of software engineering experience with large-scale system design and implementation.
  • Bachelor's degree in a relevant field such as Computer Science or Software Engineering.
  • Proven experience shipping and maintaining production-grade ML systems end-to-end.
  • Strong hands-on experience with MLOps tooling, including Ray, MLflow, Kubeflow, SageMaker, Vertex AI.
  • Proficiency in Python and familiarity with major ML frameworks like TensorFlow, PyTorch, scikit-learn.
  • Experience building CI/CD pipelines for ML workflows using tools such as Jenkins or GitHub Actions.

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