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Contract Machine Learning Software Engineer Jobs in Houston, TX

Senior Software Engineer Job Type: Contractor (~15 hours/week) Location: Remote Job Summary We are ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

Software Engineer

Houston, TX · Remote

$60 - $75/hr

Software Engineer (Remote USA) | $60-$75 per Hour Do You Want to Build Software That Shapes the ... Background in machine learning, automation, or AI-driven applications. What's In It for You?

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Collaborate with product and software engineers to integrate the features into our platform.

Lead Machine Learning Engineer

Houston, TX · Remote

$104K - $138K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Collaborate with product and software engineers to integrate the features into our platform.

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Collaborate with product and software engineers to integrate the features into our platform.

Showing results 21-40

Contract Machine Learning Software Engineer information

See Houston, TX salary details

$60.6K

$140.9K

$196.2K

How much do contract machine learning software engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for contract machine learning software engineer in Houston, TX is $140,881.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,600.00 and $165,200.00 per year, depending on experience, location, and employer.

What is a contract machine learning software engineer?

A Contract Machine Learning Software Engineer is a professional who is hired on a temporary or project basis to design, develop, and deploy machine learning models and systems. They often work with organizations that need specialized expertise for a limited duration, helping to build algorithms, analyze data, and integrate AI solutions into existing software products. Contract engineers typically have strong backgrounds in programming, mathematics, and data science, and they may work remotely or on-site. Their responsibilities can range from data preprocessing and model training to deploying models in production environments. This arrangement allows companies to access advanced machine learning skills without committing to a full-time hire.

What are the key skills and qualifications needed to thrive as a contract machine learning software engineer?

To thrive as a Contract Machine Learning Software Engineer, you need a strong background in computer science, proficiency in programming languages like Python, and expertise in machine learning algorithms, typically supported by a relevant degree or equivalent experience. Familiarity with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, along with knowledge of version control systems like Git, is essential. Strong problem-solving abilities, communication skills, and the ability to work independently or with cross-functional teams make someone stand out in this role. These skills ensure efficient delivery of scalable machine learning solutions that meet client requirements and project timelines.

How does a contract machine learning software engineer typically collaborate with full-time team members during a project?

As a Contract Machine Learning Software Engineer, you will often work closely with full-time data scientists, software engineers, and product managers. Collaboration usually happens through regular stand-up meetings, code reviews, and shared documentation platforms. Despite being a contractor, you’re expected to integrate seamlessly with the team, communicate progress transparently, and adapt to the company’s workflows. Building strong relationships and proactively seeking feedback can help ensure your contributions align with the project’s goals and timelines.

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

AspectContract Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master’s in CS, ML, or related fields; experience with ML frameworksBachelor's or Master’s in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentProject-based, often remote, focused on developing ML models and softwareData analysis, visualization, and interpretation, often in research or business settings
Employer & Industry UsageTech companies, startups, consulting firms; used for deploying ML solutionsResearch institutions, finance, healthcare, and tech; used for insights and decision-making

The main difference is that Contract Machine Learning Software Engineers focus on developing and deploying ML models as software solutions, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but their primary objectives and work environments differ.

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

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

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

The top searched job categories for Contract Machine Learning Software Engineer jobs in Houston, TX are:

Infographic showing various Contract Machine Learning Software Engineer job openings in Houston, TX as of August 2026, with employment types broken down into 94% Full Time, and 6% Temporary. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $140,881 per year, or $67.7 per hour.

Machine Learning Engineer - Remote

YO AI Labs

Houston, TX • Remote

$80 - $120/hr

Full-time

Posted 11 days ago


Job description

Senior Software Engineer

Job Type: Contractor (~15 hours/week)
Location: 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 engineering tasks using Model Context Protocol (MCP) tools.

You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.

Key Responsibilities
  • Create reinforcement learning environments for software engineering tasks.
  • Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
  • Build deterministic verification systems and golden reference solutions.
  • Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
  • Develop realistic, reproducible software engineering scenarios.
  • Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
  • Document solutions and provide clear technical feedback.
Required Skills
  • Strong proficiency in Python 3, Java, Rust, C++, or TypeScript.
  • Strong understanding of algorithms and data structures.
  • Experience with bug fixing and debugging complex software issues.
  • Proven experience in feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication.
  • Strong attention to detail.
Preferred Qualifications
  • Experience working with large-scale or distributed codebases.
  • Familiarity with AI/ML systems is a plus but not required.
  • Experience with rigorous code reviews and software engineering best practices.
  • Experience working effectively in remote or cross-functional teams.
Hiring Process
  1. Submit an application and screening questions.
  2. Complete an AI interview (~30 minutes).
  3. Complete a technical assessment, if required.
  4. Hiring Manager review.
Compensation

Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.

Availability

Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.