Job Details

Role Number: 200623701-3337

Summary

The Information Security Machine Learning (ISML) team empowers information security by harnessing patterns and insights from vast amounts of data to predict, detect, and respond; transforming reactive security into autonomous protection. It approaches this through a few main functions including solving short term problems with applied science, developing long term autonomous security solutions with cutting edge research, and building the needed infrastructure to support ML solutions for ourselves and partner teams.

We are seeking a highly motivated and independent machine learning engineer who can build, deploy, and support production machine learning services and platforms in cloud native environments.

Description

As an ML Platforms Engineer, you will help build the software stack for autonomous security cloud platforms and services. This includes the command and control, telemetry, federation, device selection and registration, and coordination functions. Working in an ML heavy environment, you will apply experience integrating machine learning inputs and outputs with service specific data to provide a highly available, low latency platform to power autonomous security in the cloud, and on device.

You will tune and deploy a wide range of machine learning models via Apple’s cloud services. These models support the training and inference capabilities for autonomous security research initiatives, and partner model integrations. In this role you will use skills across applied machine learning, distributed machine learning, and cloud technologies.

Day to day, you will leverage a continuous integration and continuous delivery to deploy the API and UI services of autonomous security and support the dynamic and diverse requirements of device based integrations, API services, and partner integrations. You will work in virtualized environments and in Apple cloud platforms using industry standard libraries and languages to tailor models to run on cloud compute and high end GPU resources. You will collaborate with others in the team to build suitable interfaces for devices, partners, and end users to interact with the models the team creates. You will also help enable agentic workflows and systems that can plan, orchestrate tools and services, and take multi-step actions so security capabilities can operate reliably and safely.

You will adapt the intelligence, models, and research developed by the team to run on macOS. Development and deployment of autonomous security on macOS needs to balance privacy, rigor, visibility, performance, and impact. In this role, you need to have skills and knowledge across a blend of macOS development best-practices, systems and software engineering, and embedded systems development.

Day to day, you will use Apple internal tools and platforms, third party cloud, and local hardware to test and deploy software, frameworks, and ML models to target current macOS and future macOS releases.

Minimum Qualifications

• 5+ years experience in technical leadership roles focused on ML systems platform engineering / infrastructure

• Hands-on with AWS or GCP, Docker/Kubernetes, and micro-services architectures.

• Experience with IaC (Pulumi, Terraform, etc.) and CI/CD pipelines.

• 5+ years experience building and running micro-services in Java, Python, or similar.

• Deployed models on GPU using CUDA and frameworks/libraries like PyTorch or TensorFlow.

• Experience with MLOps & LLMOps patterns and best practices.

• Understanding of OAuth 2.0 fundamentals (authentication, delegated authorization, etc.).

Preferred Qualifications

• Experience with SageMaker Notebooks, Endpoints, and Training.

• Experience with monitoring deployed models for performance, accuracy, drift, and reliability targets.

• Experience with MLX or other training and inference frameworks.

• Experience building agentic workflows (LangChain, Google ADK, Claude Agent SDK, etc.).

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .