Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Dallas, TX
Live, first seen by us 70 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Set MLOps standards and reusable pipeline patterns for taking models from notebook to production
Productionize models with Databricks MLflow, AutoML, Unity Catalog and Model Serving
Design and maintain CI/CD pipelines for model training, deployment and promotion
Govern model lifecycle: tracking, registration, versioning, lineage and access control
Set up model and data monitoring, validation checks and incident response for production ML
Establish the department’s MLOps standards, reusable pipeline patterns, and “golden path” for taking a model from notebook to production
Partner with data science teams to productionize models using Databricks MLflow, AutoML, Unity Catalog, and Model Serving
Design and maintain automated CI/CD pipelines for model training, deployment, and controlled promotion across environments
Govern the model lifecycle through experiment tracking, model registration, versioning, lineage, and access control
Establish model and data monitoring, validation checks, and operational observability; support incident response and reliability of production ML systems
Bachelor’s Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field
Strong proficiency in Python as a primary engineering language, with experience writing tested, maintainable production code
Strong SQL skills and working knowledge of Spark or other distributed data processing frameworks
Practical experience establishing or operating an MLOps workflow, including model deployment, pipeline automation, monitoring, and lifecycle management
Ability to explain the intuition behind common ML algorithms and follow model training, evaluation, and hyperparameter tuning best practices
Experience with Unity Catalog for model governance, lineage, and controlled promotion of ML assets
Master’s Degree in a related field
Familiarity with cloud data platforms, infrastructure-as-code, containerization and orchestration
Experience mentoring or training data scientists on engineering best practices
Required Qualifications: - Bachelor’s Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field - Must have hands-on experience with Databricks MLflow and AutoML
- Databricks certification (e.g., Databricks Certified Machine Learning Associate or Professional) - Master’s Degree in a related field - Familiarity with cloud data platforms, infrastructure-as-code, containerization and orchestration
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Day 70
Similar jobs usually come down between day 6 and day 70.
Well past Diamondback’s usual: its jobs come down by about day 24.
From 4,442 similar postings that came down, and 5 of Diamondback’s. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Three (3) to five (5) years of hands-on experience building, deploying, and operating machine learning or data-intensive systems in production - Strong proficiency in Python as a primary engineering language, with experience writing tested, maintainable production code - Strong SQL skills and working knowledge of Spark or other distributed data processing frameworks
- Strong proficiency in Python as a primary engineering language, with experience writing tested, maintainable production code - Strong SQL skills and working knowledge of Spark or other distributed data processing frameworks - Practical experience establishing or operating an MLOps workflow, including model deployment, pipeline automation, monitoring, and lifecycle management
CURRENT EMPLOYEES - Please apply using "Jobs Hub" in Workday. This career site is for external applicants only. The Machine Learning (ML) Developer is the first dedicated ML Development role in the department and is responsible for establishing the development practices, standards, and platform foundations that move machine learning models from experimentation into reliable, governed production. Working primarily within the Databricks ecosystem, the ML Developer will define how models are built, tracked, deployed, and monitored, and will coordinate with data science teams and technical professionals across the organization to ensure company objectives and goals are met. Job Responsibilities:
- Establish the department’s MLOps standards, reusable pipeline patterns, and “golden path” for taking a model from notebook to production - Partner with data science teams to productionize models using Databricks MLflow, AutoML, Unity Catalog, and Model Serving - Design and maintain automated CI/CD pipelines for model training, deployment, and controlled promotion across environments
- Bachelor’s Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field - Must have hands-on experience with Databricks MLflow and AutoML - Three (3) to five (5) years of hands-on experience building, deploying, and operating machine learning or data-intensive systems in production
- Experience with Unity Catalog for model governance, lineage, and controlled promotion of ML assets - Databricks certification (e.g., Databricks Certified Machine Learning Associate or Professional) - Master’s Degree in a related field
Complete your application on diamondbackenergy.wd12.myworkdayjobs.com. The employer’s form will show what is required.
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
CURRENT EMPLOYEES - Please apply using "Jobs Hub" in Workday. This career site is for external applicants only.
The Machine Learning (ML) Developer is the first dedicated ML Development role in the department and is responsible for establishing the development practices, standards, and platform foundations that move machine learning models from experimentation into reliable, governed production. Working primarily within the Databricks ecosystem, the ML Developer will define how models are built, tracked, deployed, and monitored, and will coordinate with data science teams and technical professionals across the organization to ensure company objectives and goals are met.
Job Responsibilities:
Include but are not limited to
Required Qualifications:
Preferred Qualifications:
Diamondback is an Equal Employment Opportunity Employer. Diamondback provides equal employment opportunities to all qualified applicants without regard to race, sex, sexual orientation, gender identity, national origin, color, age, religion, veteran or disability status, genetic information, pregnancy, or any other status protected by law. Diamondback participates in E-Verify. Learn more about E-Verify.
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Dallas, TX
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