Principal Machine Learning Engineer

Oracle

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Quick summary

Work type
On-site
Location
Nashville, TN
Salary
$126,200–$264,100 / yr
Posted
12 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $226k
This role $195k
$108k $296k
below market most similar roles pay here above market

This role pays less than 77% of similar roles. Most pay $198,000–$254,750 — the blue band above. At the midpoint, this role pays about $195k versus about $226k 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 955 open roles on FindRole.

Listed pay typically runs $102,300–$234,600 across 790 roles with salary data.

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At a glance

TL;DR · Principal Machine Learning Engineer

The Principal Machine Learning Engineer joins the Product and Research team to implement machine learning model serving for production environments. This role involves automating machine learning workflows, including data extraction, transformation, and loading, while creating infrastructure to monitor model performance and alignment with design criteria. The engineer will develop efficient, bug-free code from scratch, maintain internal tools and platforms, and provide expert troubleshooting for machine learning engineering infrastructure. Key technical requirements include proficiency with third-party machine learning frameworks, packages, and libraries such as PyTorch, TensorFlow, and Keras. The position focuses on the operational considerations of model deployment, specifically addressing scalability, stability, and maintenance. Additionally, the role involves evaluating data quality, security, and privacy issues to ensure robust production readiness and seamless integration into existing systems.

What does a Machine Learning Engineer earn?

Median $235750 from 323 postings across 48 companies.

See salary data

What you'll do

  • Implement machine learning model serving for production environments.
  • Automate ML workflows including ETL, model deployment, and continuous delivery.
  • Create infrastructure and frameworks to monitor the performance of deployed models.
  • Develop, maintain, and refine internal tools, platforms, and services.
  • Write efficient, bug-free code from scratch and maintain the existing codebase.
  • Provide expert troubleshooting and debugging support for ML engineering infrastructure.
  • Integrate open source models into new or existing systems.
  • Develop novel metrics to provide analytical insights on model performance to stakeholders.

What we're looking for

  • Applicants must be able to read, write, and speak English.
  • 6 to 10+ years of experience is required.
  • Experience implementing machine learning model serving for production environments is required.
  • Experience automating machine learning workflows, including ETL, deployment, and monitoring, is required.
  • Experience developing efficient, bug-free code from scratch and maintaining existing codebases is required.
  • Experience with third-party machine learning frameworks, packages, and libraries like PyTorch, TensorFlow, and Keras is required.
  • Experience creating infrastructure and frameworks to monitor the performance of trained models is required.
  • Experience mentoring junior team members and providing technical oversight for moderately sized projects is required.

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