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Apple Security Machine Learning Engineer Information United States, California, Cupertino 608719816
06.05.2025
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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.
- 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
- 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
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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