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

Pivotal Solutions

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Design, develop, and deploy advanced AI and machine learning models to solve complex business ... Mentor junior engineers and provide technical guidance on AI best practices, model development, and ...

Varsity Tutors

Machine Learning Tutor

Pearland, TX · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Sugar Land, TX · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Missouri City, TX · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Houston, TX · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Showing results 41-60

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

Machine Learning Engineer information

See Houston, TX salary details

$30.1K

$123K

$184.8K

How much do machine learning engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for machine learning engineer in Houston, TX is $122,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $148,000.00 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 Houston, TX?

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

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

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

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

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

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

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

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Houston, TX as of August 2026, with employment types broken down into 70% Full Time, 5% Temporary, and 25% Contract. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $122,971 per year, or $59.1 per hour.

Staff Machine Learning Engineer (Autonomy)

Mariana Minerals

Houston, TX • On-site

$160K - $200K/yr

Full-time

Re-posted 9 days ago

Job description

About Mariana Minerals
Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We're reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making.
Role Overview
We are hiring Machine Learning Engineers (Autonomy) to build the autonomy and sensor-integration software that lets our mining vehicles perceive, decide, and drive themselves.
In this role you will own parts of the software and sensor integration that enables full mining autonomy - sensor fusion across LiDAR, cameras, radar, and IMU/GNSS; perception, localization, and mapping; and the autonomy stack that turns sensing into safe vehicle motion. You will carry work from architecture and algorithm design through implementation, simulation, and bench and field validation, working hand in hand with our hardware, controls, and systems-engineering teams. This is a hands-on, first-principles role for an engineer who wants to develop the world's first fully autonomous mines.
What You'll Do
  • Develop autonomy software for autonomous mining vehicles focusing on one or more area: perception, SLAM, motion planning, and control
  • Integrate and calibrate the sensing suite (LiDAR, cameras, radar, IMU, GNSS), implementing sensor fusion and time synchronization robust to dust, vibration, and corrosion-heavy mining environments
  • Build and maintain embedded and real-time software that bridges sensing, compute, and actuation, with attention to safety, latency, and reliability
  • Develop simulation, logging, and data pipelines to test autonomy behavior and drive performance against safety and availability targets
  • Lead bench, rig, and field validation of the autonomy stack, debugging across the full software-hardware boundary
  • Collaborate with hardware and controls engineers to integrate sensing, compute, and actuation into a complete vehicle

What You'll Bring
  • Bachelor's degree in Mechatronics, Robotics, Computer Science, Electrical, or related engineering discipline
  • 5-10+ years developing autonomy, robotics, or embedded software, ideally for mobile robots or vehicles
  • Strong proficiency in C++ and/or Python, and with a robotics middleware such as ROS/ROS 2
  • Hands-on experience with sensor integration and fusion - LiDAR, cameras, radar, IMU, GNSS - and with perception, localization, or motion-planning algorithms
  • Working knowledge of real-time and embedded systems, and of the controls and software-hardware integration that drive actuation
  • Experience in autonomous vehicles, robotics, automotive, or off-highway equipment strongly preferred
Our culture is built on four principles:
Everyone Gets Home Safe. We never put speed or cost ahead of people.
Extreme Ownership. We take full responsibility for outcomes, relentlessly driving toward solutions.
Engineer Out Requirements, then Automate. We simplify, optimize, and then automate for scale.
Share Your Legos. We collaborate openly, share knowledge, and empower each other to build bigger, better solutions.
Join us as we build the future of responsible mineral sourcing and supply!

Apply