5 days ago

Sr. Machine Learning Infrastructure Engineer, Creator Studio

Apple

On Site
Full Time
$200,000
Culver City, CA

Job Overview

Job TitleSr. Machine Learning Infrastructure Engineer, Creator Studio
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$200,000
LocationCulver City, CA

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Job Description

Summary

At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly! The Creator Studio team needs your help shaping the next generation of creative editing tools by working on pioneering technologies to surprise and delight creative pros and enthusiasts alike.

As a Sr. Machine Learning Infrastructure Engineer, you will be working alongside world-class engineers and creatives to help innovate in the creative space in ways that only Apple can. This is a highly visible and impactful opportunity!

Description

In this role, you will lead the development of scalable ML data infrastructure, enabling high-quality ML model development and continuous improvement of application features for creatives.

Responsibilities

  • Identify, source and ingest multimodal datasets for model development, working backwards from a deep understanding of application features
  • Build scalable and reusable infrastructure components for data pipelines, such as labeling via human annotations or LLMs
  • Build and maintain core tooling and frameworks to support model development, including scalable storage and retrieval systems, A/B comparison visualizations and test harnesses to ensure training vs. inference-time parity
  • Partner with model development teams to manage a shared codebase, build common data processing libraries and profile/optimize ML workloads
  • Analyze real-world user interaction data to uncover gaps in training data distributions and derive model success metrics

Minimum Qualifications

  • BS/MS in Computer Science or related field with 3+ years of relevant industry experience.
  • Proficiency in a high-level programming language (preferably Python) and database query language (e.g., SQL).
  • Strong understanding of software engineering best practices, especially around data modeling, schema design and building maintainable data access layers.
  • Experience developing and optimizing large-scale ML workloads running on distributed processing frameworks.
  • Strong understanding of an ML-based product lifecycle.
  • Ability to communicate effectively and collaborate with partner teams, particularly ML research scientists and engineers.
  • Ability to solve everyday problems in innovative ways.
  • Committed to encouraging an open and inclusive work environment.

Preferred Qualifications

  • Working knowledge of modern database and distributed data processing technologies/frameworks (e.g., Spark, Dask, Ray, Presto, Parquet, Flink, Druid, Airflow, PostgreSQL).
  • Experience with Python package management and build/deployment tooling (e.g., uv, poetry, hatch).
  • Experience optimizing models and algorithms to run efficiently on resource-constrained platforms.
  • Knowledge of cloud platforms and container orchestration technologies (e.g., Kubernetes, Docker, AWS, GCP).
  • Familiarity with iOS ecosystem including the Swift programming language.
  • Familiarity with model architectures and various training techniques, particularly in the Computer Vision domain.
  • Familiarity with modern camera ISP and digital image processing algorithms and models.
  • Knowledge and keen interest in learning the art and science of photography.

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 $147,400 and $272,100, 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 seek to promote 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.

Apple accepts applications to this posting on an ongoing basis.

Key skills/competency

  • Machine Learning Infrastructure
  • Data Pipelines
  • Distributed Processing
  • ML Model Development
  • Data Modeling
  • Python Programming
  • SQL
  • Schema Design
  • A/B Testing
  • Computer Vision

Tags:

Machine Learning Infrastructure Engineer
ML infrastructure
data pipelines
model development
distributed processing
data modeling
schema design
ML workloads
data analysis
Python
SQL
Spark
Dask
Ray
Airflow
PostgreSQL
Kubernetes
Docker
AWS
Computer Vision

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How to Get Hired at Apple

  • Research Apple's innovation culture: Study their mission, values, recent product launches, and employee insights on LinkedIn and Glassdoor.
  • Tailor your resume for ML infrastructure: Highlight experience in scalable data pipelines, distributed systems, Python, and data modeling specific to machine learning at Apple.
  • Showcase impactful ML projects: Emphasize your contributions to developing and optimizing large-scale ML workloads and data solutions.
  • Prepare for in-depth technical interviews: Focus on ML system design, data architecture, distributed computing, and problem-solving skills relevant to a Sr. Machine Learning Infrastructure Engineer role.
  • Demonstrate collaboration and communication: Be ready to discuss how you've partnered effectively with ML research scientists and cross-functional teams at Apple.

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