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Machine Learning Technical Lead, Data Engineering - SIML, ISE
AppleUnited Statesfull_timeVerifiedPosted 13 Dec 2024
💰 $264,200/yr($175,800/yr – $264,200/yr)
About the role
Summary
Posted: Dec 13, 2024Weekly Hours: 40
Role Number:200583182
Do you believe Machine Learning and AI can change the world? We truly believe it can! We are the Data Team of the System Intelligence and Machine Learning (SIML) group at Apple. We build high quality ML datasets, from very small targeted sets to petabyte scale, to train and evaluate ML models that power AI-centric features for many Apple products. Our datasets help power intelligent algorithms on Camera and the Photos app, improve text input experiences (autocorrect, autocompletion, OCR) and more recently feed generative technologies in Apple Intelligence (Image Playground, Genmoji, Writing Tools, Math Notes…) We’re looking for an exceptional engineering lead who is passionate about Apple products and values; who loves working with data ops at scale; and who is committed to the hard work vital to continuously improve complex ML data pipelines and data infrastructure. AI-centric products are the future of software; at their core, data is the source code of AI, a key component of innovation and inclusive and fair ML products. We invite you to join us at this exciting time; grow fast and positively impact multiple critical features on your first day at Apple!
Description
Our SIML Data team focuses on acquiring, synthesizing, annotating, and ensuring the quality of ML data, driving numerous features in collaboration with R&D teams in Apple’s SWE organization. As a data engineering tech lead, you will be responsible for establishing and executing the strategy for our organization’s ML data engine. In this position, you will: - Collaborate with a variety of partners, from infrastructure, ML research teams to our data functions, including data engineers, to assess the needs - Identify state of the art data components used to store, expose and track ML data - Identify opportunities for improvement of internal infrastructure offerings, and influence roadmaps of partner teams to build or improve key components we rely on - Design and execute the roadmap for adoption of new components, build the pipelines necessary to connect data systems and teams - Improve automation workflows, data visualization tools, ML enrichment, asset lineage tracking, including data coming from sophisticated synthetic workflows, data governance and compliance components, storage and tracking of synthetic data - Be hands on, actively participate to the stack and implement high quality code
Minimum Qualifications
- Bachelors, Masters or PhD in Computer Science, Mathematics, Physics, or a related field; or equivalent practical experience.
- 7+ years of industry experience as a software engineer, including 2+ years as a tech lead/architect specialized in data infrastructure
- Proven experience designing, automating and scaling large data pipelines (petabyte scale desired) using state of the art technologies
- Expertise in Python or another modern programming language
- Strong ability to design and lead a technical roadmap, work with cross functional teams and a diversity of profiles, proven capacity to influence and build alignment
Preferred Qualifications
- Demonstrated prior experience in foundation models such as building data infrastructure supporting generative technologies
- Self-starter, able to handle ambiguity, identify risks, mitigate, and autonomously find the right people and tools to get the job done
- Proven track record of mentoring and growing engineers, lift the level of software engineering excellence in a ML data ops team typically focused on short term deliveries
Pay & Benefits
- At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $175,800 and $264,200, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are elig
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