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Machine Learning Developer Jobs in Texas (NOW HIRING)

PROS Holdings, Inc.

Machine Learning Engineer II

Houston, TX · On-site

$93.10K - $127.50K/yr

Machine Learning Engineer II About PROS: PROS, Inc. is the leading offer management provider to the airline industry, helping airlines deliver seamless retail experiences designed to maximize revenue ...

Oxy

AI Machine Learning Engineer

Houston, TX · On-site

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

Intuit

Staff Machine Learning Engineer

Plano, TX

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

PROS

Machine Learning Engineer II

Houston, TX · On-site

$93.10K - $127.50K/yr

Machine Learning Engineer II About PROS: PROS, Inc. is the leading offer management provider to the airline industry, helping airlines deliver seamless retail experiences designed to maximize revenue ...

Intuit

Staff Machine Learning Engineer

Plano, TX

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

Oxy

AI Machine Learning Engineer

Houston, TX

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154.20K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154.20K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154.20K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Vanguard

Machine Learning Engineer, Specialist

Dallas, TX

$113.30K - $136K/yr

Performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment. Leverages detailed understanding of ...

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Machine Learning Developer information

See Texas salary details

$17

$35

$48

How much do machine learning developer jobs pay per hour?

As of May 29, 2026, the average hourly pay for machine learning developer in Texas is $35.79, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $48.37 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Developer, and why are they important?

To excel as a Machine Learning Developer, you need a strong background in mathematics, statistics, programming (especially Python), and a relevant degree in computer science or related fields. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), version control systems, and cloud platforms is typically required, as are certifications in data science or AI. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data findings into actionable solutions. These skills and qualities are essential to develop accurate models, collaborate with stakeholders, and drive innovation in a rapidly evolving field.

What are some common challenges faced by Machine Learning Developers when deploying models to production environments?

Machine Learning Developers often encounter challenges such as ensuring model scalability, managing data drift, and integrating models with existing systems during deployment. Another frequent hurdle is monitoring model performance in real time and retraining models as new data becomes available. Collaborating closely with data engineers, DevOps, and software developers is essential to streamline the deployment pipeline and maintain model reliability in production.

What does a Machine Learning Developer do?

A Machine Learning Developer designs, builds, and implements machine learning models and systems that enable computers to learn from data without explicit programming. They work with large datasets, select appropriate algorithms, and optimize models for various tasks such as predictions, classifications, and recommendations. Their responsibilities often include data preprocessing, feature engineering, model evaluation, and deploying models into production environments. Machine Learning Developers typically collaborate with data scientists, software engineers, and business teams to deliver AI-powered solutions.

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

AspectMachine Learning DeveloperData Scientist
CredentialsBachelor's or Master's in CS, ML, or related fields; certifications like TensorFlow or AWS MLBachelor's or Master's in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentDevelops and deploys ML models in software or cloud environmentsAnalyzes data, builds models, and provides insights for decision-making
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsUsed across industries for data analysis, predictive modeling, and insights

Both roles require strong programming skills and knowledge of ML algorithms. Machine Learning Developers focus on building and deploying models in production environments, while Data Scientists analyze data to inform business decisions. The roles often overlap but differ mainly in their primary focus and end goals.

What are popular job titles related to Machine Learning Developer jobs in Texas? For Machine Learning Developer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Developer jobs in Texas look for? The top searched job categories for Machine Learning Developer jobs in Texas are:
Machine Learning Developer jobs near you
Infographic showing various Machine Learning Developer job openings in Texas as of May 2026, with employment types broken down into 60% Full Time, 16% Part Time, 18% Contract, 3% Nights, and 3% Summer. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution, with an average salary of $74,449 per year, or $35.8 per hour.
Machine Learning Engineer II

Machine Learning Engineer II

PROS Holdings, Inc.

Houston, TX • On-site

$93.10K - $127.50K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Machine Learning Engineer II
About PROS:
PROS, Inc. is the leading offer management provider to the airline industry, helping airlines deliver seamless retail experiences designed to maximize revenue and margin growth. Powered by AI, the PROS Platform enables commercial teams to align capacity with demand and coordinate pricing, merchandising and offer strategies to construct and market optimal offers in real time. By optimizing every customer interaction, PROS helps airlines improve revenue performance and quality, increase commercial agility, attract more customers and build lasting loyalty. Learn more at pros.com.
Day in the Life of the Machine Learning Engineer II:
PROS is seeking a Machine Learning Engineer II to build, deploy, and operate scalable machine learning solutions within the PROS Platform. This role focuses on productionizing ML models, optimizing performance at a scale, and owning well-defined ML components while collaborating closely with data scientists and software engineers.
  • Design, implement, and productionize machine learning models and data pipelines in collaboration with data scientists and engineers.
  • Convert research and prototype workflows into scalable, reliable, and secure production systems.
  • Build and optimize distributed ML pipelines for large-scale training and low-latency inference.
  • Apply ML best practices for feature engineering, model tuning, validation, and performance optimization.
  • Deploy, monitor, and maintain ML systems in production; diagnose and resolve performance and reliability issues.
  • Evaluate existing ML pipelines and recommend improvements to architecture, tooling, and processes.
  • Extend and optimize shared ML libraries and frameworks to support reuse and consistency.
  • Partner with software engineers to integrate ML solutions into the platform and meet SLA requirements.

Required Qualifications - About you:
  • 5+ years of progressively responsible experience (including time spent to pursue advanced degree) in machine learning engineering or data-intensive software engineering.
  • Strong proficiency in Python and experience building production-grade ML systems.
  • Hands-on experience with distributed data and ML frameworks such as PySpark, Databricks, and MLflow.
  • Experience with deep learning frameworks (TensorFlow and/or PyTorch).
  • Strong understanding of distributed systems, performance tuning, and cost optimization.
  • Experience deploying, monitoring, and maintaining ML models for batch and real-time inference.
  • Familiarity with Linux environments and cloud platforms, preferably Microsoft Azure.
  • Strong communication skills and ability to work independently on well-defined problems.

Highly Preferred:
  • Advanced degree in Computer Science, Machine Learning, Data Science, or a related field.
  • Experience with GPU-accelerated training or inference.
  • Exposure to advanced ML techniques and large-scale optimization problems.
  • Experience improving shared ML platforms, tooling, or libraries used across teams.

AI Fluency & Growth Mindset - We welcome candidates who:
  • Understand core AI concepts and apply them ethically to enhance productivity, insights, and decision-making.
  • Craft effective prompts to optimize the quality and relevance of AI-generated outputs.
  • Explore and apply agentic AI systems, using or managing autonomous agents to streamline workflows and automate tasks.
  • Leverage AI tools to boost efficiency, creativity, and innovation in their daily work.
  • Stay curious and adaptable, continuously experimenting with AI-driven solutions to elevate team performance and customer impact.

Why Join PROS?
PROS culture and its extraordinary people are at the core of our success. We are passionate about what we do and relentless in delivering on our promises.
Our commitment to customer success inspires us to think smarter and dream bigger, empowering airlines to achieve more than they ever imagined through intelligent offer and revenue optimization.
At PROS, we foster a culture of care, where people feel supported to grow, innovate, and bring their best selves to work-every day. From flexible ways of working to continuous learning, we empower our teams to thrive both personally and professionally.
Join PROS, a dedicated travel technology company with nearly 40 years of proven airline expertise and a long runway for future growth, now powering the future of AI-driven airline retailing. If you want to be part of something exceptional, help us shape how airlines compete, innovate, and win.
PROS Core Values
  • We are Owners

We look for every opportunity to create a better PROS and a better experience for our customers - and we hold ourselves accountable.
  • We are Innovators

We think creatively to find new paths to success - for our people, our customers and our business.
  • We Care

We are centered on caring for the people, businesses, and communities we serve.

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