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Machine Learning Assistant Jobs in Richmond, TX (NOW HIRING)

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 ... Proven experience designing and shipping chatbots, virtual assistants, or agentic systems using ...

Lead Machine Learning Engineer

Houston, TX · Remote

$104K - $138K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Proven experience designing and shipping chatbots, virtual assistants, or agentic systems using ...

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 ... Proven experience designing and shipping chatbots, virtual assistants, or agentic systems using ...

AI/ML Engineer (Eng - Senior) Cementing

Houston, TX · On-site +1

$99K - $137K/yr

Develop and maintain data pipelines, datasets, and documentation to support scalable AI solutions. * Assist with the deployment, monitoring, and continuous improvement of machine learning models and ...

AI/ML Engineer (Eng - Senior) Cementing

Houston, TX · On-site +1

$99K - $137K/yr

Develop and maintain data pipelines, datasets, and documentation to support scalable AI solutions. * Assist with the deployment, monitoring, and continuous improvement of machine learning models and ...

... assistants, computer vision, cognitive services, and big data tools used to manage large datasets * Experience applying artificial intelligence (AI), machine learning (ML), and advanced data ...

AI Engineer III

Houston, TX · On-site

$124K - $132K/yr

Design, develop, and deploy scalable machine learning models (predictive, classification, anomaly detection, clustering) and AI-powered solutions such as intelligent assistants, forecasting systems ...

Design, develop, and deploy scalable machine learning models (predictive, classification, anomaly detection, clustering) and AI-powered solutions such as intelligent assistants, forecasting systems ...

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Machine Learning Assistant information

See Richmond, TX salary details

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How much do machine learning assistant jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for machine learning assistant in Richmond, TX is $14.70, according to ZipRecruiter salary data. Most workers in this role earn between $13.32 and $15.67 per hour, depending on experience, location, and employer.

What are some common challenges a machine learning assistant may face when supporting data preparation and model training?

Machine Learning Assistants often encounter challenges such as cleaning large, unstructured datasets, identifying and handling missing or inconsistent data, and ensuring data privacy compliance. They also need to communicate effectively with data scientists and engineers to understand project requirements and adapt to evolving priorities. Staying organized and managing multiple tasks simultaneously—such as data preprocessing, feature engineering, and running model experiments—is crucial for success in this role.

What is a machine learning assistant?

A Machine Learning Assistant is a professional who supports the development, implementation, and maintenance of machine learning models and systems. They assist data scientists and engineers by preparing datasets, conducting preliminary data analysis, running experiments, and helping to optimize algorithms. This role often involves coding, testing models, and ensuring the quality and reliability of machine learning solutions. Machine Learning Assistants play a key role in streamlining workflows and enabling faster progress in AI projects.

What are the key skills and qualifications needed to thrive as a machine learning assistant?

To thrive as a Machine Learning Assistant, a solid background in mathematics, statistics, programming (often Python), and foundational knowledge of machine learning algorithms is essential, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems such as Git is commonly required. Strong problem-solving abilities, attention to detail, and the capability to communicate findings effectively are standout soft skills in this role. These skills ensure accurate data analysis, effective model building, and successful collaboration within multidisciplinary teams.

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

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

What are popular job titles related to Machine Learning Assistant jobs in Richmond, TX?

For Machine Learning Assistant jobs in Richmond, TX, the most frequently searched job titles are:

What job categories do people searching Machine Learning Assistant jobs in Richmond, TX look for?

The top searched job categories for Machine Learning Assistant jobs in Richmond, TX are:

What cities near Richmond, TX are hiring for Machine Learning Assistant jobs?

Cities near Richmond, TX with the most Machine Learning Assistant job openings:

Infographic showing various Machine Learning Assistant job openings in Richmond, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $30,582 per year, or $14.7 per hour.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Houston, TX

Full-time

Posted 25 days ago


Job description

Application Deadline: September 1, 11:59pm EST

Program Summary - Commercial Technology Internships

Company Overview:

Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.

Position Overview:

CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.

Responsibilities:

  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:

  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.