Machine Learning Technical Lead, Data Engineering - SIML, ISE

Cupertino, California, United States

Apple

We’re a diverse collective of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways.

View all jobs at Apple

Apply now Apply later

Summary

Posted: Dec 13, 2024
Weekly 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 eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

    Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.



  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.




Apply now Apply later
Job stats:  0  0  0

Tags: Computer Science Data governance DataOps Data pipelines Data visualization Engineering Machine Learning Mathematics ML models OCR PhD Physics Pipelines Python R R&D Research

Perks/benefits: Career development Equity / stock options Health care Relocation support

Region: North America
Country: United States

More jobs like this