Tech Lead Machine Learning Engineer - Finance Digital Transformation

Apple Inc

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Work type
On-site
Location
Austin, TX
Posted
37 days ago

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How this pay compares to similar roles

Similar $221k
$172k most similar roles pay here $270k

This listing doesn't post a salary. Most similar roles pay $195,000–$246,150.

Based on 239 similar postings.

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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TL;DR · Tech Lead Machine Learning Engineer - Finance Digital Transformation

As a Tech Lead Machine Learning Engineer at Finance Digital Transformation, you will serve as the technical lead for product cost within Apple’s Operations Finance organization. This role involves overseeing solution design and guiding engineers in developing scalable data models and pipelines using SQL and big data technologies. You will collaborate with cross-functional teams including data and software engineers, product managers, and program managers to operationalize AI solutions from prototype to production. Key responsibilities include instilling strong engineering practices, explaining technical concepts to non-technical stakeholders, and ensuring rapid and reliable delivery of value through MLOps/LLMOps practices on cloud platforms like AWS, GCP, or Azure. The ideal candidate has a graduate degree in computer science or related fields, seven years of experience building data-driven solutions, and expertise in Python, DRY principles, modularity, testing standards, and version control systems.

What you'll do

  • Oversee solution design and guide engineers as technical lead.
  • Operationalize AI solutions from prototype to production efficiently.
  • Instill strong engineering practices in team machine learning processes.
  • Rapidly deliver value to the Finance organization through reliable systems.
  • Translate technical concepts for non-technical stakeholders effectively.
  • Develop scalable data pipelines using SQL and big data technologies.
  • Apply ML algorithms for regression, classification, and anomaly detection.

What we're looking for

  • Graduate degree in computer science, data science, math, quantitative finance, or related field.
  • Seven or more years of experience building data-driven solutions.
  • Expertise in leading engineers, collaborating cross-functionally, and explaining technical concepts to non-technical audiences.
  • Proficiency in SQL, big data technologies, and data ops best practices for scalable pipelines.
  • Experience developing Python applications with DRY principles, modularity, testing standards, version control, code review, and front-end development.
  • Applied experience with ML algorithms, generative AI, agentic solutions, MLOps/LLMOps, CI/CD, drift monitoring, and cloud platforms.

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