Machine Learning Developer

Aimlroles; Texas; On-site; USD 120,000 - 155,000; Full time

Job summary

Diamondback is seeking a Machine Learning Developer to establish ML development practices and platform foundations for production-grade models. You will work primarily in the Databricks ecosystem to define how models are built, tracked, deployed, and monitored, coordinating with data science teams across the company.

You will design CI/CD pipelines, govern the model lifecycle, ensure data quality, and drive adoption of shared ML tooling.

Qualifications

• 3–5 years of hands-on experience building, deploying, and operating ML systems in production.
• Strong Python and SQL with experience in distributed data processing.
• Experience establishing or operating an MLOps workflow including deployment, monitoring, and lifecycle management.
• Proficiency with Git, unit testing, CI/CD, and production-grade coding standards.
• Ability to explain ML concepts and follow training, evaluation, and tuning best practices.
• Excellent collaboration across data science, engineering, and business teams.

Responsibilities

• Establish MLOps standards, reusable pipelines, and a production-ready path from notebook to deployment.
• Partner with data science teams to productionize models using Databricks MLflow and AutoML.
• Design and maintain CI/CD pipelines for model training, deployment, and controlled promotion.
• Govern model lifecycle with experiment tracking, registration, lineage, and access control.
• Establish model and data monitoring, validation checks, and production reliability.
• Enforce data quality and schema validation for trusted model inputs.
• Author documentation, architectures, and playbooks; lead code reviews.
• Coordinate with stakeholders to define requirements and drive framework adoption.
• Evaluate emerging tools and AI patterns for ML delivery improvements.

Skills

Python

SQL

Databricks MLflow

AutoML

CI/CD

Git

Spark

MLOps

Model Deployment

Model Monitoring

Education

Bachelor’s Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics

Master’s Degree (preferred)

Tools

Unity Catalog

Databricks

Job description

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

• 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
• Enforce data and feature quality, schema validation, and data versioning so models train and infer on trusted inputs
• Author documentation, reference architectures, and playbooks; lead code reviews and knowledge-sharing to drive consistent engineering practice
• Coordinate with business stakeholders, data scientists, data engineers, and IT to define requirements and drive adoption of shared frameworks
• Evaluate emerging tools and patterns, including agentic and LLM-assisted development workflows, and recommend improvements to ML delivery

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
• 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
• Practical experience establishing or operating an MLOps workflow, including model deployment, pipeline automation, monitoring, and lifecycle management
• Software engineering fundamentals including version control (Git), unit testing, CI/CD, and common design patterns
• Ability to explain the intuition behind common ML algorithms and follow model training, evaluation, and hyperparameter tuning best practices
• Strong interpersonal, analytical, and communication skills, with the ability to work effectively across data science, engineering, and business teams

Preferred Qualifications:

• 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
• Familiarity with cloud data platforms, infrastructure-as-code, containerization and orchestration
• Exposure to LLM/GenAI application patterns such as RAG and evaluation harnesses, and to agentic or AI‑assisted development workflows
• Experience mentoring or training data scientists on engineering best practices
• Ability to operate both independently and as part of a team
• Self-starter requiring minimal supervision with strong organizational and time management skills

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 aboutE-Verify.