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Machine Learning Engineer Opt Jobs in Houston, TX

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

Missouri City, TX · Remote

$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

$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

Pearland, TX · Remote

$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

$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 ...

Veracity Software Pvt. Ltd.

AI Lead

Houston, TX · On-site

Required : • Proven experience as an AI Engineer, Machine Learning Engineer, or similar role, with a portfolio of delivered AI/Gen AI solutions. • Proficiency in AI platforms and tools such as ...

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

Machine Learning Engineer Opt information

See Houston, TX salary details

$30.1K

$123K

$184.8K

How much do machine learning engineer opt jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning engineer opt 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 into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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

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

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

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

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

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

Machine Learning Engineer Opt jobs near you
Infographic showing various Machine Learning Engineer Opt job openings in Houston, TX as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 22% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $122,971 per year, or $59.1 per hour.

Senior AI Engineer

Houston, TX • On-site

Pivotal Solutions
See more jobs at Pivotal Solutionsexternal

$99K - $137K/yr

Full-time

Re-posted 27 days ago

Job description


Responsibilities
  • Design, develop, and deploy advanced AI and machine learning models to solve complex business problems across diverse domains.
  • Collaborate with cross-functional teams, including data scientists, product managers, and software engineers, to integrate AI solutions into production systems.
  • Optimize AI pipelines for performance, scalability, and reliability, ensuring efficient processing of large-scale datasets.
  • Drive innovation by researching and implementing cutting-edge AI techniques, frameworks, and tools to enhance product capabilities.
  • Mentor junior engineers and provide technical guidance on AI best practices, model development, and deployment strategies.
  • Monitor and maintain AI systems in production, ensuring robust performance and rapid response to issues.

Requirements
Qualifications
  • Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
  • 5+ years of experience as an AI Engineer, Machine Learning Engineer, or similar role, with a proven track record of delivering impactful AI solutions.
  • Expertise in AI/ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and the end-to-end AI development lifecycle, including data preprocessing, model training, and deployment.
  • Strong programming skills in Python and proficiency with relevant libraries (e.g., NumPy, Pandas, Scikit-Learn, Hugging Face).
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes) for deploying AI models.
  • Excellent problem-solving skills and the ability to translate business requirements into technical solutions.
  • Strong communication and collaboration skills, with experience working in agile, cross-functional teams.

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