AIML - Systems Engineer for ML Infra, Applebot Crawl & Knowledge Graph at Apple

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

27 Jan, 26

Salary

0.0

Posted On

29 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Algorithms, Data Structures, Distributed Systems, Cloud-Native Environment, Large-Scale Data Processing, Micro-Service Architecture, Containerized Environment, Observability Tools, Machine Learning, Natural Language Processing, Web Data Extraction, Data Pipelines, Docker, Kubernetes, Spark, Cassandra

Industry

Computers and Electronics Manufacturing

Description

Apple’s Knowledge Infrastructure powers features across a variety of Apple products including Siri, Spotlight, Safari, Messages and Lookup. The Knowledge Infrastructure team works on creating and maintaining the pipelines to build the Knowledge Graph which integrates data assets from various heterogeneous sources into a unified knowledge representation, interacting with Web data sources and large language models to power advanced retrieval augmented generation features. We work on problems at the intersection of large scale data management and machine learning, while deploying solutions to a modern cloud-based infrastructure with an advanced technology stack. DESCRIPTION Apple’s Knowledge Platform team is looking for a talented, result-oriented, creative problem-solver System Engineer who can help manage and maintain large-scale, data-driven systems to enable the growth of the Knowledge Platform. As a member of this team you will be responsible for deploying and monitoring micro-services and pushing the envelop of large scale retrieval augmented generation systems. You will work on building large scale Web data extraction pipelines, and you will also be responsible for managing and deploying self-serve features allowing teams across Apple to use Knowledge Infrastructure. You will be working with bleeding-edge ML technologies to train, deploy and test large scale models that solve a number of problems at the intersection of data pipelines and natural language processing. MINIMUM QUALIFICATIONS Bachelor's or Master's degree in Computer Science or equivalent work experience. Background in computer science: algorithms, data structures, and distributed systems Experience working in a cloud-native environment such as AWS Experience working with large-scale data processing pipelines (Spark, Cassandra, etc.) Experience with micro-service architecture in a containerized environment (Docker, Kubernetes, etc.) Experience with observability tools for monitoring applications (Prometheus, DataDog, etc.) PREFERRED QUALIFICATIONS Experience with training and fine-tuning large language models is a plus Experience with Scala and Go is a plus Excellent interpersonal skills, able to work independently as well as in a team

Responsibilities

As a Systems Engineer, you will manage and maintain large-scale, data-driven systems to support the Knowledge Platform. You will deploy and monitor micro-services and build large-scale web data extraction pipelines.