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Contract Machine Learning Software Engineer Jobs in Houston, TX

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the ...

bp

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

Role Summary We are looking for a Senior Machine Learning Engineer who combines deep machine learning expertise with strong software engineering discipline to design, build, and deploy production ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$116K - $154K/yr

... software engineers to ensure reliable, scalable adoption across the business • Communicate ... machine learning or statistical models, with a proven track record of delivering end-to-end ...

BravoTech

Software Engineer I

Houston, TX · On-site

Contract?(W2) We are seeking a Software Engineer to work closely with business analysts and ... Exposure to machine learning, forecasting, optimization, or statistical modeling techniques.

YO AI Labs

Senior Software Engineer - Remote

Texas City, TX · Remote

$104K - $138K/yr

Senior Software Engineer Job Type: Contract Location: Remote Job Summary: In this role, you'll ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Vitol

Software Engineer in Data Science

Houston, TX · On-site

$109K - $131K/yr

Vitol is the world's largest independent energy and commodities trading company, and they are seeking an experienced Software Engineer to join their global data science and machine learning team. The ...

Scalence L.L.C.

AI ML Software Engineer

Houston, TX · On-site

C. is a company focused on AI and machine learning solutions, and they are seeking an AI ML Software Engineer. The role involves designing, developing, and deploying AI/ML solutions while ...

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Showing results 1-20

All JobsContract Machine Learning Software Engineer JobsContract Machine Learning Software Engineer Jobs in Houston, TX

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 Jul 28, 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.

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 key skills and qualifications needed to thrive as a Contract Machine Learning Software Engineer, and why are they important?

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.

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 popular job titles related to Contract Machine Learning Software Engineer jobs in Houston, TX? For Contract Machine Learning Software Engineer jobs in Houston, TX, the most frequently searched job titles 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:
Contract Machine Learning Software Engineer jobs near you
Infographic showing various Contract Machine Learning Software Engineer job openings in Houston, TX as of July 2026, with employment types broken down into 93% Full Time, and 7% 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.

Software Engineer, Machine Learning Infrastructure

Bot Auto

Houston, TX • On-site

$165K - $195K/yr

Other

Posted 19 days ago

Job description

Company Introduction

At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.

We are seeking a highly skilled and motivated Software Engineer to design, develop, and scale our machine learning annotation, evaluation, and training infrastructure. This role is central to the quality and velocity of our perception and ML models - from curating and managing high-quality annotated datasets, to building robust evaluation pipelines that drive continuous model improvement. The ideal candidate combines strong systems engineering skills with a deep understanding of ML Workflows/Ops and large-scale data infrastructure.

Key Responsibilities

Machine Learning & Deep Learning Infrastructure

  • Evaluation Platform - Architect and own a scalable, end-to-end model evaluation platform for perception and prediction models central to autonomous driving. Define metrics, design for scale, and make results actionable for researchers.
  • Training Infrastructure - Partner with research scientists to optimize and scale distributed training workflows. Integrate experiment tracking and reproducibility into the model lifecycle from day one.
  • Dataset & Feature Store - Design and maintain a versioned, high-quality training data store that accelerates model development and supports rapid iteration.
  • ML Pipelines - Build automated pipelines spanning data preparation, model training, validation, and deployment - enabling fast experimentation and reproducible outcomes.
  • Annotation Platform - Contribute to tooling and infrastructure that powers high-throughput, high-accuracy data annotation at scale.
  • MLOps - Develop production ML services that treat models as products - with reliability, observability, and continuous improvement built in.

Data Infrastructure

  • Maintain and evolve a robust data storage and access layer (S3 data lake, Delta Lake) underpinning annotation, evaluation, and training workflows.
  • Build scalable, reliable data collection pipelines supporting diverse vehicle dispatch missions.
  • Develop foundational services and packages that provide clean, performant access to autonomous driving data across the stack.
Qualifications

Required:

  • Educational Background: Bachelor's or Master's in Computer Science, or equivalent practical experience.
  • Strong Programming Skills: Strong proficiency in Python; working knowledge of C++
  • ML/DL Infrastructure Experience - Demonstrated hands-on experience building or scaling at least one of the following in a production environment:
    • Evaluation platforms - automated model benchmarking, metric computation, and regression tracking across model versions.
    • Training infrastructure - distributed training pipelines, experiment tracking, and model lifecycle management (e.g. W&B, MLflow, ClearML).
    • Dataset curation & feature stores - versioned dataset management, data lineage, and tooling for high-quality training data at scale.
    • Annotation platforms - tooling or pipelines that support high-throughput, high-accuracy labeling workflows.
  • Distributed Systems - Strong experience with distributed computing and container orchestration - Kubernetes, Spark, or comparable frameworks.
  • Ability to operate independently: scope ambiguous problems, make sound architecture decisions, and drive them to completion.

Preferred:

  • C++ experience in performance-sensitive or safety-critical applications
  • Full-stack service development experience.
  • Prior work in autonomous driving or robotics.

Apply