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
83 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $228k
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 $200,437–$254,750 — the blue band above. At the midpoint, this role pays about $195k versus about $228k 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 and productionize machine learning models. This role involves transforming prototypes into production-ready solutions by scaling models, cleaning code, and ensuring high production quality standards. Key responsibilities include automating machine learning workflows from ETL to deployment, creating infrastructure to monitor model performance, and developing novel metrics for non-technical stakeholders. The engineer will evaluate data quality, security, and privacy issues while providing troubleshooting support for ML infrastructure. Technical requirements include proficiency with machine learning frameworks such as PyTorch, TensorFlow, and Keras. The position requires developing efficient, bug-free code from scratch and maintaining professional documentation for experimentation and data collection to solve complex modeling and operational challenges within the production environment.

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 models for production by transforming prototypes into production-ready systems.
  • Automate ML workflows including data extraction, transformation, loading (ETL), and deployment monitoring.
  • Create infrastructure and frameworks to monitor the performance of deployed models against design criteria.
  • Evaluate and mitigate risks related to data quality, security, and privacy in modeling processes.
  • Develop, maintain, and refine internal tools, platforms, and services for machine learning operations.
  • Write efficient, bug-free code from scratch while maintaining high standards for version control and documentation.
  • Provide expert troubleshooting and debugging support for machine learning infrastructure and workflows.
  • Mentor junior team members and contribute to the talent pipeline through candidate interviews.

What we're looking for

  • Must have 6 to 10+ years of experience in the field.
  • Proficiency in machine learning frameworks such as PyTorch, TensorFlow, or Keras is required.
  • Ability to read, write, and speak English is required.
  • Experience implementing machine learning models for production and automating ML workflows including ETL processes.
  • Ability to develop efficient, bug-free code from scratch and maintain existing codebases.
  • Capability to create infrastructure and frameworks to monitor the performance of deployed machine learning models.
  • Ability to evaluate data quality, security, and privacy issues while performing data cleaning and preprocessing.
  • Experience in mentoring junior team members and participating in candidate interviews.

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