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 Senior Software Engineer - Applied Machine Learning (Search) - Cupertino, California, United States

   
Job information
Posted by: Apple 
Hiring entity type: Retail 
Work authorization: Not Specified for United States
Position type: Direct Hire, Full-Time 
Compensation: ******
Benefits: See below
Relocation: Not specified 
Position functions: Computers - Software Engineer
 
Travel: Unspecified 
Accept candidates: from anywhere 
Languages: English - Fluent
 
Minimum education: See below 
Minimum years experience: See below 
Resumes accepted in: English
Cover letter: No cover letter requested
Job code: 200155037 / Latpro-3734792 
Date posted: Mar-21-2020
State, Zip: California, 95014

Description

Senior Software Engineer - Applied Machine Learning (Search)

Santa Clara Valley (Cupertino) , California , United States

Software and Services

Summary

Posted: Mar 20, 2020

Weekly Hours: 40

Role Number: 200155037

Imagine what you could do here. At Apple, great 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. Apple's Applied Machine Learning team has built systems for a number of large-scale data science applications. We work on many high-impact projects that serve various Apple lines of business. We use the latest in open source technology and as committers on some of these projects, we are pushing the envelope. Working with multiple lines of business, we manage many streams of Apple-scale data. We bring it all together and extract the value. We do all this with an exceptional group of software engineers, data scientists, dev-ops engineers and managers.

Key Qualifications

  • 3+ years of experience working in Search domain
  • 5+ years of experience working in java and web services
  • Meticulous attention to detail and dedication to quality; Excellent written and oral communication skills on both technical and non-technical topics
  • Extensive hands-on experience building solutions for large-scale internet infrastructure; with emphasis on Search and Recommender systems
  • Solid understanding of Solr cloud or Elastic search
  • Solid understanding of Spark, Kafka, Flume and distributed systems like Hadoop and Cassandra
  • Analyze, measure and evaluate the search ranking quality in the production system
  • Hand on experience on Query understanding and tokenization.
  • Identify and define various ways of search integration with new line of businesses
  • Extensive hands-on experience in implementing multi tenant scalable web services
  • Extensive hands-on experience in implementing large scale data ingestion pipeline

Description

Join Apple's AML Team, as an Search Software engineer. You will work with other search engineers in the team for overall success for Search and other ML based systems. Collaborate with peers from other Engineering groups, MarCom, AppleCare and operations teams to solve complex and challenging problems with efficient and scalable delivery of Search solutions. You are expected to be self-motivated, dedicated, and a solution-oriented individual. The main responsibilities for this position include: - Lead engineering effort to deliver best-in-class Search solutions for Apple - Design the architecture and implementation of Search solution. - Define and build pipeline to ingest, process and tag search data - Define and build pipeline to capture implicit and explicit feedback to evaluate search quality - Identify gaps and define the solution to implement those gaps. - Work with other engineering teams within Apple to build high quality solution. Other aspects of the job include mentoring and providing feedback to junior developers, working with the team manager and PM in estimating scope and team capacity, responding to urgent requests from executives or business needs, and maintaining the stability and high reliability of our systems.

Education & Experience

Technical BS/MS/PHD or relevant industry experience.

Additional Requirements





Requirements

See job description

 

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