Machine Learning Engineer, Information Security

Apple • Sunnyvale, CA

2d

About The Position

Join Apple’s Information Security Machine Learning (ISML) team, where we are
redefining cybersecurity through data-driven intelligence. Our mission is to
transform traditional reactive security measures into autonomous systems that
proactively detect and defend against threats. We achieve this through
cutting-edge research, applied science, and robust infrastructure development.
We are seeking a highly motivated and talented Machine Learning Engineer to join
our dynamic and growing team. You will play a pivotal role in designing,
developing, and deploying machine learning models that power our advanced
security products and services. This is an incredible opportunity to make a real
world impact by building intelligent systems that detect and prevent advanced
threats, enhance critical security processes, and protect Apple and our
customers. We're looking for a passionate and highly skilled macOS engineer to
join our team and build the foundation for autonomous security on Apple devices.
This role requires a deep understanding of the macOS environment and a proven
ability to develop and deploy high-performance applications.

The Security ML Engineer will bring their expertise in machine learning to the
problems and opportunities facing Information Security at Apple. You will
contribute to the Autonomous Security program by developing production ready
AI/ML systems using Apple’s internal platforms, cloud services, and local
compute environments. You will translate research to design, building and
deploying machine learning models for security use cases, leveraging generative
AI, statistical modeling, reinforcement learning, and data science to address
complex security challenges. You will collaborate with cross-functional teams
including security teams, software engineers, and researchers to prototype and
scale AI/ML driven security solutions. You will own end-to-end ML workflows:
data exploration, model development, evaluation metrics design, deployment, and
monitoring.

Requirements

• BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field.
• Strong programming skills in Python and Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, and Scikit-learn.
• Hands-on experience with full ML model lifecycle: from experimentation to deployment and monitoring.
• Solid grasp of security fundamentals including network security, incident response, threat modeling, and vulnerability management.
• Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences.
• Familiarity with CI/CD workflows and ML pipelines .
• Experience operating, and scaling production services in cloud native environments.
• Experience deploying models on CUDA devices using tools like TensorFlow or Torch.
• Proven experience building generative AI applications for real-world use cases.

Nice To Haves

• Ph.D. in a technical field such as Computer Science, Engineering, Statistics, or related disciplines.
• In-depth knowledge of ML algorithms, including supervised/unsupervised learning, deep learning (CNNs, RNNs, LSTMs), and large language models.
• Industry experience in deploying ML and generative AI solutions in cybersecurity contexts.
• Familiarity with cloud platforms (e.g., AWS, GCP) and their security offerings is a plus.
• Experience with large scale data processing and analysis using tools such as Apache Spark.
• Experience working in a key security process, such as Incident Response, Threat Intelligence, or Vulnerability Management.
• Experience with specific security tools and technologies (e.g., SIEM, IDS/IPS, endpoint security solutions).
• Contributions to open-source security or machine learning projects.
• Publications or talks at top-tier ML or security conferences.
• Additional proficiency in C++ or Swift is a plus

Responsibilities

• Developing production ready AI/ML systems using Apple’s internal platforms, cloud services, and local compute environments.
• Translating research to design, building and deploying machine learning models for security use cases, leveraging generative AI, statistical modeling, reinforcement learning, and data science to address complex security challenges.
• Collaborating with cross-functional teams including security teams, software engineers, and researchers to prototype and scale AI/ML driven security solutions.
• Owning end-to-end ML workflows: data exploration, model development, evaluation metrics design, deployment, and monitoring.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level