The Information Security Machine Learning (ISML) team empowers security services 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 the solutions for ourselves and partner teams. We are seeking a highly motivated and talented Security 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.

DESCRIPTION

This Security ML Engineer will bring their expertise in security and machine learning to the problems and opportunities facing Information Security at Apple, leveraging statistical, reinforcement learning, generative AI, and data science techniques to build unique solutions to security problems. You will also develop, adapt, and deploy models and machine learning technologies in support of the Autonomous Security program. Day to day, you will work with other ML engineers, security teams, software developers, and cross functional teams to prototype, validate, deploy, and maintain machine learning models and services to support the security needs and initiatives of Apple. You will be deep in the data, identifying key data sets, assessing for quality and suitability for machine learning, cleaning and processing for the problem at hand, and apply statistic analysis to the data to aid in scoping and building a solution. You will design and test evaluation metrics. You will use Apple internal tools and platforms, local hardware, and cloud platforms to test and deploy ML models to achieve security goals and outcomes. Working with the Machine Learning Research team, you will also bring prototype and experimental solutions to production, applying state-of-the-art techniques to existing and emerging security problems.

MINIMUM QUALIFICATIONS

• Bachelor’s or Masters (preferred) degrees in Machine Learning, Data Science, Computer Science, Information Security,Mathematics, Statistics, or related field, with a focus on machine learning and cybersecurity
• Proficiency in Python and Scala, and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch, etc)
• Experience with some or all of the model lifecycle, from prototyping and development, to deployment, monitoring, and operations
• Solid understanding of fundamental security concepts, including network security , incident response, threat modeling, and vulnerability management.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Experience with a CI/CD software development lifecycle and machine learning pipelines
• Experience building, operating, and maintaining production services in cloud native environments
• Experience designing and implementing database schemas for service data storage
• Experience with CUDA, Torch, or TensorFlow, and production deployment of models to CUDA devices

PREFERRED QUALIFICATIONS

• Understanding of machine learning algorithms and techniques, including: Supervised learning (classification, regression) Unsupervised learning (clustering, anomaly detection) Deep learning (CNNs, RNNs, LSTMs)
• Experience in building and deploying machine learning models in an enterprise, preferably in a security-related domain
• Experience building and deploying ML solutions within security products or services.
• Familiarity with cloud platforms (e.g., AWS, GCP) and their security services is a plus.
• Experience with large-scale data processing and analysis using tools like Spark or similar.
• 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 presentations at security or machine learning conferences.
• Proficiency in C++, or Swift

Please refer the Job description for details