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Machine Learning Engineer Jobs in Prosper, TX (NOW HIRING)

YO AI Labs

Machine Learning Engineer - Remote

Dallas, TX · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software ...

Resolve Tech Solutions

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

Develop machine learning models and algorithms to address business needs. Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions. Clean ...

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Showing results 41-60

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Prosper, TX

Machine Learning Engineer information

See Prosper, TX salary details

$28.8K

$117.9K

$177.2K

How much do machine learning engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for machine learning engineer in Prosper, TX is $117,925.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,000.00 and $141,900.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs

What are the most commonly searched types of Machine Learning Engineer jobs in Prosper, TX?

The most popular types of Machine Learning Engineer jobs in Prosper, TX are:

What are popular job titles related to Machine Learning Engineer jobs in Prosper, TX?

For Machine Learning Engineer jobs in Prosper, TX, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Prosper, TX look for?

The top searched job categories for Machine Learning Engineer jobs in Prosper, TX are:

What cities near Prosper, TX are hiring for Machine Learning Engineer jobs?

Cities near Prosper, TX with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Prosper, TX as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $117,925 per year, or $56.7 per hour.

Machine Learning Developer

Diamondback Energy

Dallas, TX • On-site

Full-time

Posted 7 days ago

Diamondback Energy rating

8.7

Company rating: 8.7 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

9th of 87 rated oil and gas companies

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 about E-Verify.

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