About the position
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something. As part of Apple Intelligence, Siri team is at the forefront of the next revolution in machine learning and Generative AI. We are dedicated to creating groundbreaking conversational assistant technologies for both large-scale systems and new client devices, building upon our legacy of intelligent assistant solutions that already assist millions of users worldwide. Does the opportunity to play a part in building groundbreaking technology for large-scale systems, natural language and artificial intelligence excite you? Do you want to expand the experience of Siri and other AIML products to new products that will help millions get things done, across the globe? Join the ML Systems Evaluation Engineering (MLSEE) team at Apple and contribute to a highly accomplished team that evaluates AIML products, that will delight and inspire millions of people!
Responsibilities
- Participate in engineering design discussions and be responsible for the end user experience.
- Focus on automating and optimizing processes across the software development lifecycle to improve collaboration, deployment frequency, and system reliability for ML Evaluations Platform.
- Work both collaboratively and independently in a rapidly changing environment with ever-changing priorities.
- Ensure that applications serve users in the best possible manner.
Requirements
- 10+ years of relevant industry experience.
- 3+ years leading large scale, complex projects or teams as a DevOps / Infrastructure engineer or tech lead.
- Extensive experience with CI/CD Pipeline Management: Design, implement, and maintain CI/CD pipelines to automate testing, integration, and deployment of code.
- Strong experience in Cloud Infrastructure Management, i.e. managing and optimizing cloud services such as AWS, GCP, etc.
- Strong proficiency in at least one programming language (e.g., Python, Go, Java).
- Extensive experience in Containerization and Orchestration using Docker or Kubernetes.
- Good understanding of System Reliability and Performance, able to design and implement systems for high availability, disaster recovery, and fault tolerance.
Nice-to-haves
- Good exposure to setting up monitoring and logging with tools such as Splunk, Prometheus, Grafana, Nagios.
- Strong problem-solving skills and ability to work independently.
- Passion for supporting internal partners like research/ML modeling to understand their needs.
- Excellent communication skills to build consensus with stakeholders, both internally and externally.
- Obsessed with distributed systems at scale, infrastructure reliability, scalability, security, and continuous improvement.
- Experience developing systems using rolling, zero-downtime deploys.
- Strong networking fundamentals and proficiency in debugging network related issues.
- Experience managing, deploying and optimizing Pub/Sub systems, queuing systems, and streaming platforms (such as Apache Kafka, Amazon Kinesis, Apache Flink, etc.).
