Summary
Posted: Mar 5, 2025
Weekly Hours: 40
Role Number:200593335
Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The Product Marketing Customer Analytics team is seeking DevOps engineers in Austin to build an analytics platform to support customer analytics with advanced, scalable and robust architecture, tools, data products, and critical data pipelines that are optimized for rapid business intelligence, data analysis, and data science. In this role, you will be responsible for building and maintaining our team's analytics platform and tools. This is a green-field opportunity to define requirements and build solutions to improve the management of overall tech stack. The DevOps Engineer will: Provide strong DevOps leadership to engineering team, project manager, and management. Develop, maintain, and be responsible for the platform health, scaling and planning Developing self-service tools and automating things to improve data engineering efficiency. Visualize and champion the right use of the platform by building intelligent telemetry. Play a critical part in implementing a secure, robust and high availability DevOps pipeline Implement push button deployment at scale with zero downtime Automate build & deployment processes
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Description
- Champion zero-downtime deployment process through continuous delivery practices, rapidly releasing features that provide insights on platform health. - Design, implement, and maintain scalable AWS cloud architectures to support AI model training and hosting. - Deploy, monitor, and optimize AI/ML models using services such as Amazon SageMaker, EC2, Lambda, and EKS. - Develop and manage CI/CD pipelines for efficient deployment and integration of AI applications. - Ensure high availability, security, and compliance of cloud-based AI systems. - Collaborate with data scientists, software engineers, and product teams to streamline the model deployment lifecycle. - Implement observability tools, logging, and monitoring using CloudWatch, Splunk, Prometheus, or Grafana. - Provision and optimize ML platforms such as Dataiku and distributed AI frameworks like Ray. - Manage and optimize GPU-based infrastructure for high-performance AI workloads. - Troubleshoot performance and scaling issues in cloud environments. - Develop and maintain infrastructure-as-code (IaC) scripts using tools like Terraform, Ansible, or Puppet to automate the provisioning and configuration of infrastructure resources. - Experience with cloud platforms such as AWS, Azure and working in both on-prim and hybrid cloud setup. - Proficient with containerization and cluster management technologies like Docker and Kubernetes. - Excellent with Python, Bash, PERL, or other scripting languages. - Experience working in an agile scrum and also an ability to work independently. - Able to quickly learn new and existing technologies. - Strong attention to detail and excellent analytical capabilities.
Minimum Qualifications
- 5+ years of experience in DevOps, software engineering
- BS in Computer Science Quantitative Finance, Math, Physics or a related Engineering degree
Preferred Qualifications
- Strong expertise in AWS services (EC2, S3, Lambda, RDS, SQS, IAM, etc.).
- Hands-on experience with AI model hosting and container orchestration using Docker and Kubernetes.
- Proficiency in CI/CD tools like Jenkins, GitHub Actions, GitLab CI, or AWS CodePipeline.
- Experience with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation.
- Knowledge of networking, security best practices, and monitoring solutions.
- Strong scripting skills in Python, Bash, or Go.
- Experience with ML platform provisioning and optimization (e.g., Dataiku, Ray, GPU-based training environments).
- Experience with back-end frameworks like Spring and Hibernate.
- Experience with UI/UX frameworks like React and Angular.
- Unix and Linux System administration experience: ssh, monitoring processes, attaching storage, cleaning disk space, tailing logs, etc.
- Experience with modern web services architectures. Experience with infrastructure automation, especially Terraform. Experience with relational database systems, including SQL and relational design.
- Candidates must demonstrate strong skills with collaboration, negotiation, and influencing and must be able to work in multi-functional projects with internal partner engineering teams.
- Familiarity with MLOps best practices is a plus.
- MS in Computer Science Quantitative Finance, Math, Physics or a related Engineering degree
Additional Requirements
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- 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.