Principal Machine Learning Engineer

Oracle

Quick summary

Work type
On-site
Location
Austin, TX
Salary
$114,600–$234,600 / yr
Posted
9 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $227k
This role $175k
$97k most similar roles pay here $283k

This role pays less than 85% of similar roles. Most pay $197,631–$256,000 — the shaded band above. At the midpoint, this role pays about $175k versus about $227k for comparable roles.

Based on 240 similar postings.

Employer

About Oracle

Oracle Corporation is a leading multinational technology company specializing in database software, cloud computing, and enterprise software.

Oracle currently has 607 open roles on FindRole.

Listed pay typically runs $97,500–$209,500 across 467 roles with salary data.

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At a glance

TL;DR · Principal Machine Learning Engineer

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As a Principal Machine Learning Engineer in Oracle Cloud Infrastructure's AI Infrastructure organization, you will lead the development of advanced training infrastructure for large GPU clusters and design agentic systems at enterprise scale. Your day-to-day responsibilities include designing robust software architectures using Java, Python, and other languages, participating in the full software lifecycle from development to production operations, and contributing to cutting-edge research on Generative AI models. You will work with multi-modal data generation frameworks and collaborate closely with product managers to enhance coding standards and foster an inclusive engineering culture. Essential skills include experience with distributed systems, cloud architecture best practices, and hands-on knowledge of Kubernetes and Docker for building highly available services. This role demands a strong background in system design and the ability to deliver impactful solutions in fast-paced environments.

Skills

Python Java Kubernetes Docker CI/CD Oracle Cloud Infrastructure Generative AI Transformer models Attention mechanism Prompt tooling Scalable distributed systems Fault-tolerant software systems Service-oriented design patterns Containers Modern IaaS building blocks Structured logging Instrumentation for metrics

What you'll do

  • Design and develop AI software using Java, Python, and other languages.
  • Build distributed, scalable, fault-tolerant systems for Generative AI model development.
  • Apply engineering principles to define robust architectures for bleeding-edge GPU clusters.
  • Participate in the full lifecycle of model development from training to evaluation.
  • Contribute to coding standards and enhance inclusive engineering culture within the team.
  • Identify requirements, scope solutions, estimate work, and schedule deliverables effectively.

What we're looking for

  • 6+ years of experience building and shipping enterprise distributed or cloud-native systems.
  • Strong foundation in system design, distributed systems, and cloud architecture best practices.
  • Proficiency in Java, Python, or similar object-oriented languages.
  • Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal models.
  • Hands-on experience with containers and orchestration technologies like Kubernetes and Docker.
  • Proven ability to deliver impact in collaborative, fast-paced environments.

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