Machine Learning Cloud Engineer, Information Security
Apple
SummaryPosted: Oct 14, 2024Role Number:200573132The 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 within AIS with applied science, developing long term autonomous security solutions with groundbreaking research, and building the needed infrastructure to support the solutions for ourselves and partner teams. We are seeking a highly motivated and independent machine learning cloud engineer that can build, support production machine learning services and products in cloud native environments. DescriptionDescriptionAs an ML Cloud Engineer, you will build the software stack for autonomous security cloud 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 robust, highly available platform to power autonomous security in the cloud, and on device. You will design, adapt, and deploy a wide range of machine learning models via Apple’s cloud services. These models support the hybrid ML capabilities of on-device models, 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, to provide high availability, low latency services, model training, and inference. Day to day, you will use a continuous integration and continuous delivery pattern 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 get along with the models the team creates. Minimum QualificationsMinimum QualificationsExperience with running machine learning tasks on cloud computeSkilled in cloud technologies such as AWS or GCP, container technologies such as Docker and Kubernetes, and Microservices.Experience with building and running micro services using Java, Python, Go, Elixir or a similar languageExperience with a CI/CD software development lifecycle and machine learning pipelinesExperience building, operating, and maintaining production services in cloud native environmentsExperience designing and implementing database schemas for service data storageExperience with CUDA, Torch, or TensorFlow, and production deployment of models to CUDA devicesKey QualificationsKey QualificationsPreferred QualificationsPreferred QualificationsDemonstrated design, implementation, and delivery of cloud GPU services to perform inference at scaleExperience with AWS EKS or other Kubernetes servicesExperience with monitoring deployed models for performance, drift, and Service Level ObjectsExperience with MLOps or MLSREEducation & ExperienceEducation & ExperienceAdditional RequirementsAdditional RequirementsPay & BenefitsPay & BenefitsAt Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $166,600 and $250,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
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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Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
More
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.
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