Finance Digital Transformation - Senior Machine Learning Engineer

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$181,100–$272,100 / yr
Posted
21 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $213k
This role $227k
$160k most similar roles pay here $284k

This role pays more than 63% of similar roles. Most pay $179,197–$246,150 — the shaded band above. At the midpoint, this role pays about $227k versus about $213k for comparable roles.

Based on 239 similar postings.

Employer

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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At a glance

TL;DR · Finance Digital Transformation - Senior Machine Learning Engineer

As a senior machine learning engineer on the Finance Digital Transformation team, you will be responsible for building and enhancing infrastructure and services that support an effective Machine Learning practice within a highly regulated environment. Your daily tasks include extending platform capabilities for generative AI and agentic workflows, defining service level objectives, and improving observability across the ML stack. You will also develop frameworks for agentic AI, harden CI/CD practices with testing and monitoring, and ensure robustness in compliance with Finance governance standards. The role requires expertise in feature stores, registries, experiment tracking, model serving, Kubernetes, cloud platforms, and a strong understanding of regulatory requirements such as SOX. Additionally, familiarity with LLMOps and experience in corporate finance or supply chain management is beneficial.

What you'll do

  • Extend and improve existing generative AI and machine learning inference platforms.
  • Define SLOs, enhance observability, and strengthen operational readiness across ML stack.
  • Develop and deploy frameworks for agentic AI, focusing on evaluation and knowledge management.
  • Harden CI/CD practices with testing, drift monitoring, and deployment safeguards.
  • Ensure robust, auditable, and scalable controls within Finance governance frameworks.

What we're looking for

  • Bachelor’s degree (CS, data science, engineering) with 7+ years of relevant experience.
  • Proven track record of enhancing and expanding AIML platforms and services.
  • Hands-on expertise in ML platforms including feature stores, registries, experiment tracking, and model serving.
  • Strong operational skills with a focus on debugging and observability.
  • Experience in CI/CD and MLOps practices, including testing and deployment guardrails.
  • Proficiency in Kubernetes and cloud platform operations for production environments.

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