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Associate Machine Learning Government Jobs in Texas

Diamondbackenergy

Machine Learning Developer

Dallas, TX · On-site

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 ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

... modules and machine learning models as part of an AI pipeline * Works with data and software ... Due to government contract requirements, applicants are able to get clearance are preferred

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

... modules and machine learning models as part of an AI pipeline * Works with data and software ... Due to government contract requirements, applicants are able to get clearance are preferred

CACI

Machine Learning Engineer

San Antonio, TX · Hybrid

Machine Learning Engineer Job Category: Science Time Type: Full time Minimum Clearance Required to ... Federal Government contract labor categories and contract wage rates, relevant prior work ...

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All JobsAssociate Machine Learning Government JobsAssociate Machine Learning Government Jobs in Texas

Associate Machine Learning Government information

What is the difference between Associate Machine Learning Government vs Data Scientist Government?

AspectAssociate Machine Learning GovernmentData Scientist Government
Required CredentialsBachelor's degree in CS, Data Science, or related field; some roles may require certifications in ML or AIBachelor's or Master's in Data Science, Statistics, or related; certifications like CAP or DASCA are common
Work EnvironmentGovernment agencies, research labs, or defense sectors; focus on ML model development and deploymentGovernment agencies, policy analysis, research; focus on data analysis, modeling, and insights
Employer & Industry UsageFederal, state, or local government; defense, intelligence, or public servicesGovernment departments, research institutions, public policy agencies

Associate Machine Learning Government and Data Scientist Government roles often overlap in credentials and work environment, but the former emphasizes ML model development, while the latter focuses on broader data analysis and insights within government sectors.

What are the most commonly searched types of Machine Learning Government jobs in Texas?

The most popular types of Machine Learning Government jobs in Texas are:

What are popular job titles related to Associate Machine Learning Government jobs in Texas?

For Associate Machine Learning Government jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Associate Machine Learning Government jobs in Texas look for?

The top searched job categories for Associate Machine Learning Government jobs in Texas are:

What cities in Texas are hiring for Associate Machine Learning Government jobs?

Cities in Texas with the most Associate Machine Learning Government job openings:

Associate Machine Learning Government jobs near you
Infographic showing various Associate Machine Learning Government job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 2% Contract, and 1% Nights. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Machine Learning Developer

Diamondbackenergy

Dallas, TX • On-site

Full-time

Posted 7 days ago

Job description

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

  • 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.

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