Apple-posted 3 months ago
Senior
Santa Clara, CA
5,001-10,000 employees

Join us in enabling the next generation of intelligent experiences in Apple’s products and services with the latest advancements in Generative AI and Large Language Models! We are seeking a highly skilled Senior Software Engineer to join our dynamic team. This role will focus on designing, building, and maintaining large-scale distributed systems to support the end-to-end machine learning (ML) lifecycle. The ideal candidate for this position is an experienced software engineer with a strong background in backend development and API design. They should be skilled in building scalable, high-performance RESTful services and have a proven track record of implementing APIs that serve SDKs and front-end user interfaces. This candidate should have understanding both the architectural challenges and practical aspects of deploying and maintaining services in cloud environment. Your ideas will power next generation AI features, and impact hundreds of millions of people worldwide in their daily lives!

  • Design and build large-scale distributed systems to support the ML lifecycle.
  • Integrate various internal ML systems and frameworks to orchestrate ML processes.
  • Partner closely with product managers and partner teams to understand requirements.
  • Deliver innovative solutions based on requirements.
  • Design and deploy large-scale micro-services in third party cloud.
  • Bachelors in Computer Science, engineering, or a related field.
  • Demonstrated ability in software engineering with a focus on distributed systems.
  • Proven experience in building complex micro-services.
  • Proficiency in programming languages such as Python, Java, or Go.
  • Hands-on experience with relational databases or non-relational databases (e.g. PostgresSQL, MongoDB).
  • Familiarity with event-driven architectures and message brokers (e.g. Kafka, RabbitMQ).
  • Solid understanding of software engineering principles, design patterns, and RESTful service design.
  • Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • Strong communication and collaboration abilities.
  • Advance degrees in Computer Science, engineering, or a related field.
  • Familiarity with ML tools and frameworks (e.g., TensorFlow, PyTorch, MLflow).
  • Experience with CI/CD processes and tools.
  • Experience with MLOps practices and tools.
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