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

BP

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

You will apply machine learning science as a core discipline -- developing novel algorithms and ... Strong stakeholder management and ability to influence across teams and organisations. * Continuous ...

New

Apex Systems

US|Machine Learning Engineer V

Houston, TX · On-site

Job#: 3040809 US|Machine Learning Engineer V Location: Houston, Texas Role Overview We are seeking ... Use Ansible as an abstraction layer to manage complex, large-scale Azure environments. * Support ...

Talentry, LLC

Be Seen First

Machine Learning Guru (Autonomous Navigation)**

Houston, TX · Remote

$200K - $300K/yr

Manage the full life cycle of machine learning projects, including data analysis and model verification. * Collaborate with product, simulation, and algorithm teams to integrate machine learning ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$116K - $154K/yr

They are seeking an experienced Machine Learning Engineer to join their data science and machine ... management • Genuine intellectual curiosity about commodities markets, global energy flows, and ...

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

Machine Learning Manager information

See Houston, TX salary details

$48.7K

$78K

$112.7K

How much do machine learning manager jobs pay per year?

As of Jul 24, 2026, the average yearly pay for machine learning manager in Houston, TX is $78,029.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,000.00 and $88,300.00 per year, depending on experience, location, and employer.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and their role involves understanding algorithms, data processing, and model deployment. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and overseeing complex AI solutions, making complete replacement unlikely in the near term.

What are some of the main challenges a Machine Learning Manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning manager or director, often involving leadership, advanced technical skills, and strategic responsibilities. These roles usually require extensive experience, expertise in AI tools and frameworks, and may include performance-based bonuses or stock options that contribute to the total compensation. Such salaries are common in large tech companies or organizations with significant AI investments.

What are the key skills and qualifications needed to thrive as a Machine Learning Manager, and why are they important?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

Is ML a high paying job?

Machine Learning Managers typically earn high salaries due to the specialized skills required, such as expertise in algorithms, programming, and data analysis. Compensation varies based on experience, location, and industry, but it is generally above average compared to many other tech roles.

Which 3 jobs will survive AI?

Machine Learning Managers will continue to be essential as they oversee AI projects, interpret complex data, and coordinate teams, tasks that require strategic thinking and human judgment. Roles that involve creative problem-solving, emotional intelligence, and domain-specific expertise, such as healthcare professionals, educators, and skilled tradespeople, are also likely to persist despite AI advancements. These jobs rely on human intuition and adaptability that AI cannot fully replicate.

What are Machine Learning Managers?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.
What are the most commonly searched types of Machine Learning jobs in Houston, TX? The most popular types of Machine Learning jobs in Houston, TX are:
What are popular job titles related to Machine Learning Manager jobs in Houston, TX? For Machine Learning Manager jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Manager jobs in Houston, TX look for? The top searched job categories for Machine Learning Manager jobs in Houston, TX are:
What cities near Houston, TX are hiring for Machine Learning Manager jobs? Cities near Houston, TX with the most Machine Learning Manager job openings:
Machine Learning Manager jobs near you
Infographic showing various Machine Learning Manager job openings in Houston, TX as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $78,029 per year, or $37.5 per hour.
Data Science Machine Learning Internship (Summer 2027)

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Houston, TX

Full-time

Posted 2 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.

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