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Apple Machine Learning Engineering Manager - Apple Store Online 
India, Karnataka, Bengaluru 
845795313

Yesterday
Description
To be successful, you need a strong machine learning background, proven software development skills, a love of learning, and to collaborate well in multi-disciplinary teams. You will need to exhibit strong communication and leadership skills, an ability to set priorities, and an execution focus in a multifaceted environment. Responsibilities: - Attract, hire, and inspire a diverse world-class engineering team, fostering a culture of innovation, collaboration, and excellence- Stay up-to-date with emerging technologies, industry trends, and advancements in ML practices to identify opportunities for improvement and innovation and effectively communicate with stakeholders, providing regular updates on project status, progress, and any potential risks or challenges.
Minimum Qualifications
  • 10+ years related experience in enterprise applications with 5+ years of managing large engineering teams
  • Excellent leadership skills with a demonstrated ability to build, mentor and manage high-performing engineering teams.
  • Prior experience collaboratively working and effectively communicating with geographically distributed teams, partners and leaders
  • You can actively participate in investigations into realtime and offline analysis, and draw conclusions from data, recommend actions
Preferred Qualifications
  • PhD or Masters in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience
  • Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture
  • Experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc)
  • Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems