Machine Learning Cloud Engineer, Information Security (apple)
apple Seattle, United States
2024-10-27
Job posting number: #153452 (Ref:apl-200573132)
Job Description
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 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.
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.
Description
As 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.
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 Qualifications
- Experience with running machine learning tasks on cloud compute
- Skilled in cloud technologies such as AWS or GCP, container technologies such as Docker and Kubernetes, and Microservices.JOB IS FROM: italents.netVIEW
- Experience with building and running micro services using Java, Python, Go, Elixir or a similar language
- 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
Key Qualifications
Preferred Qualifications
- Demonstrated design, implementation, and delivery of cloud GPU services to perform inference at scale
- Experience with AWS EKS or other Kubernetes services
- Experience with monitoring deployed models for performance, drift, and Service Level Objects
- Experience with MLOps or MLSRE
