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Embedded Machine Learning Internship Jobs in Manvel, TX

Crowe LLP

Machine Learning Intern

Houston, TX

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

Crowe LLP

Machine Learning Intern

Houston, TX · On-site

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

Chevron Corporation

AI Engineer

Houston, TX · On-site

$120 - $180/hr

Experience implementing machine learning frameworks and libraries. * Development experience with ... be embedded within larger frameworks or applications. * Proficient at orchestrating large-scale ...

ConocoPhillips

Intern, Commercial 2027

Houston, TX · On-site

The internship offers a Commercial orientation, an exciting project assignment, and multiple opportunities to work with our Commercial management team. The internship will culminate with a ...

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Embedded Machine Learning Internship information

See Manvel, TX salary details

$24K

$40.1K

$82.8K

How much do embedded machine learning internship jobs pay per year?

As of Aug 27, 2026, the average yearly pay for embedded machine learning internship in Manvel, TX is $40,062.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,600.00 and $43,300.00 per year, depending on experience, location, and employer.

What is an embedded machine learning internship?

An Embedded Machine Learning Internship is a temporary position designed for students or recent graduates to gain hands-on experience in developing and deploying machine learning algorithms on embedded systems. These internships typically involve working with hardware such as microcontrollers, sensors, or edge devices, and using specialized tools to optimize machine learning models for low-power and resource-constrained environments. Interns collaborate with engineers and data scientists to create efficient, real-world AI solutions that run directly on devices rather than relying on cloud computing. This role helps bridge the gap between theoretical machine learning concepts and practical implementation on embedded platforms.

What are some typical projects or tasks I might work on during an embedded machine learning internship?

During an Embedded Machine Learning Internship, you can expect to work on projects such as optimizing machine learning models to run efficiently on hardware with limited resources, integrating AI algorithms into embedded systems (like microcontrollers or IoT devices), and performing real-time data processing. You'll likely collaborate closely with software engineers and hardware designers to test models on physical devices, debug performance issues, and contribute to documentation. These experiences provide practical exposure to the challenges of deploying AI in real-world, resource-constrained environments and help build skills valuable for a future career in embedded AI.

What are the key skills and qualifications needed to thrive as an embedded machine learning intern, and why are they important?

To thrive as an Embedded Machine Learning Intern, you need a background in computer science, electrical engineering, or a related field with strong programming skills in C/C++ and Python, as well as foundational knowledge of machine learning algorithms. Experience with embedded systems development tools (such as ARM Cortex, Raspberry Pi, or Arduino), version control systems, and familiarity with ML frameworks like TensorFlow Lite or Edge Impulse is often required. Analytical thinking, problem-solving ability, and effective teamwork are vital soft skills for success in this role. These skills and qualities are crucial for efficiently developing, optimizing, and deploying machine learning solutions on resource-constrained embedded platforms.

What cities near Manvel, TX are hiring for Embedded Machine Learning Internship jobs?

Cities near Manvel, TX with the most Embedded Machine Learning Internship job openings:

Embedded Machine Learning Internship jobs near you
Infographic showing various Embedded Machine Learning Internship job openings in Manvel, TX as of June 2026, with employment types broken down into 2% Internship, 14% Full Time, 80% Part Time, 3% Temporary, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $40,062 per year, or $19.3 per hour.

Data Science Machine Learning Internship (Summer 2027)

Houston, TX

Castleton Commodities International LLC
Oil and Gas Extraction • 501 - 1,000 employees
Learn more about Castleton Commodities International LLCexternal

Full-time

Re-posted 6 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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