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

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

Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps * Customize ...

New

... machine learning, and artificial intelligence solutions for industrial and production engineering applications. Focus on building scalable, production-grade analytical systems that support predictive ...

New

... machine learning, and artificial intelligence solutions for industrial and production engineering applications. Focus on building scalable, production-grade analytical systems that support predictive ...

... machine learning, and artificial intelligence solutions for industrial and production engineering applications. Focus on building scalable, production-grade analytical systems that support predictive ...

... machine learning, and artificial intelligence solutions for industrial and production engineering applications. Focus on building scalable, production-grade analytical systems that support predictive ...

Showing results 41-60

Machine Learning Engineer information

See Conroe, TX salary details

$27K

$110.2K

$165.7K

How much do machine learning engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for machine learning engineer in Conroe, TX is $110,243.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,900.00 and $132,700.00 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.

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

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

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

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

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

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

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

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

Infographic showing various Machine Learning Engineer job openings in Conroe, TX as of September 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $110,243 per year, or $53 per hour.

Machine Learning Researcher - PhD Intern (US)

Houston, TX • On-site

$4.5K - $5.8K/wk

Other

Re-posted 29 days ago


Job description

Job Description

At Citadel, our mission is to be the most successful investment team in the world. Machine Learning Researchers play a key role in this mission by developing next-generation models and trading approaches for a range of investment strategies. You'll get to challenge the impossible in quantitative research by applying sophisticated and complex statistical techniques to financial markets, some of the most complex data sets in the world.

Your Objectives

  • Use statistics, machine learning (e.g. deep learning, NLP) to extract patterns from various kinds of datasets through innovative and rigorous research
  • Implement algorithms in high-quality code
  • Work with large data sets, including unconventional and unstructured data sources
  • Back-test models and document research findings

Your Skills & Talents

  • PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field
  • Advanced training and a strong research track record in machine learning, statistics, deep learning, natural language processing, artificial intelligence, or a closely related quantitative field
  • Prior experience working in a data driven detailed research environment
  • Hands on programming experience in Python or C++
  • A background demonstrating strong problem-solving skills
  • An ability to communicate advanced concepts in a concise and logical way
  • Proficiency in creating and using algorithms to meticulously investigate and work through large data or error-checking problems

Opportunities available in New York, Miami, Greenwich, and Houston.

In accordance with applicable law, the base salary range for this role is $4,500 to $5,800 per week.

About Citadel

Citadel is one of the world's leading alternative investment managers. We manage capital on behalf of many of the world's preeminent private, public and nonprofit institutions. We seek the highest and best use of investor capital in order to deliver market leading results and contribute to broader economic growth. For over 30 years, Citadel has cultivated a culture of learning and collaboration among some of the most talented and accomplished investment professionals, researchers and engineers in the world. Our colleagues are empowered to test their ideas and develop commercial solutions that accelerate their growth and drive real impact.