Finance Digital Transformation - Senior Machine Learning Engineer

Apple Inc

Quick summary

Work type: On-site
Location: Austin, TX
Posted: 21 days ago

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How this pay compares to similar roles

Similar $213k

$161k most similar roles pay here $267k

This listing doesn't post a salary. Most similar roles pay $176,712–$249,750.

Based on 240 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 969 open roles on FindRole.

Listed pay typically runs $163,300–$272,100 across 756 roles with salary data.

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At a glance

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

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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 day-to-day tasks include extending existing generative AI platforms, improving agentic workflows, and ensuring robust operational practices across the ML stack. You will collaborate closely with delivery engineering teams to identify pain points and prioritize improvements while adhering to strict regulatory compliance standards such as SOX. The role requires expertise in feature stores, registries, experiment tracking, model serving, CI/CD pipelines, and MLOps practices, along with hands-on experience in Kubernetes and cloud platforms. Additionally, familiarity with corporate finance processes and production-level generative AI solutions is highly valued.

Skills

CI/CD Kubernetes GitOps MLOps Python Terraform AWS Docker Prometheus Grafana PostgreSQL Feature Stores Model Registries Experiment Tracking Generative AI Agentic Workflows LLMOps RAG Infrastructure Prompt Versioning SOX Compliance

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 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

7+ years of hands-on experience improving AIML platforms and services.
Extensive experience with ML platforms including feature stores, registries, experiment tracking, and model serving.
Strong background in CI/CD and MLOps practices, familiar with GitOps methodologies.
Production-level expertise with Kubernetes and cloud platforms.
Demonstrated ability to develop and deploy agentic AI frameworks and solutions.
Robust understanding of regulatory compliance within corporate finance environments.

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