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Internship Machine Learning Hardware Jobs in Texas

Socket.dev

Machine Learning Engineer, OIS-Core Engine

Austin, TX · On-site

$143.70 - $194.40/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Do you want to solve complex network management problems using machine learning to improve ... non-internship design or architecture (design patterns, reliability and scaling) of new and ...

Socket.dev

Robotics Machine Learning Engineer

Houston, TX · On-site

$120 - $180/hr

... hardware that has touched the stars, worked miles below the surface of the ocean, and even roamed ... We're looking for a Machine Learning Engineer to drive our machine learning strategy. We are ...

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Internship Machine Learning Hardware information

What is the difference between Internship Machine Learning Hardware vs Internship Data Scientist?

AspectInternship Machine Learning HardwareInternship Data Scientist
Required CredentialsBasic knowledge of hardware, electronics, and programmingStatistics, programming, and data analysis skills
Work EnvironmentHardware labs, electronics workshops, manufacturing settingsOffice, data analysis environments, cloud platforms
Employer & Industry UsageTech companies, hardware manufacturers, research labsTech firms, finance, healthcare, consulting
Common Search & Comparison IntentUnderstanding hardware-focused roles in ML projectsData analysis and modeling roles in ML

Internship Machine Learning Hardware focuses on developing and optimizing hardware components for ML systems, while Internship Data Scientist emphasizes analyzing data and building models. Both roles are essential in AI development but differ in skills, environment, and industry application.

What is an internship in machine learning hardware?

An Internship in Machine Learning Hardware is a temporary position for students or recent graduates to gain hands-on experience working with the physical components and systems that enable machine learning applications. Interns typically assist in designing, testing, and optimizing hardware such as GPUs, TPUs, or custom accelerators that run machine learning algorithms efficiently. This role often involves collaboration with software engineers and researchers to improve the performance and energy efficiency of machine learning models. The internship provides valuable exposure to both hardware engineering and the rapidly evolving field of artificial intelligence.

What are the key skills and qualifications needed to thrive as an internship in machine learning hardware, and why are they important?

To thrive as an Internship Machine Learning Hardware, you need a solid foundation in computer engineering, electrical engineering, or computer science, with coursework or experience in machine learning and hardware design. Familiarity with hardware description languages (like Verilog or VHDL), Python, C++, and tools such as TensorFlow, PyTorch, or FPGA development environments is typically required. Strong problem-solving abilities, eagerness to learn, and effective teamwork and communication skills help interns excel in multidisciplinary environments. These competencies are crucial for contributing to hardware-accelerated machine learning solutions and collaborating efficiently with engineering teams.

What kinds of projects and responsibilities can I expect during an internship in machine learning hardware?

As an intern in Machine Learning Hardware, you can expect to work on tasks such as benchmarking hardware performance for AI workloads, supporting the development and testing of new accelerator architectures, and optimizing hardware-software integration for machine learning models. You'll often collaborate with both hardware engineers and machine learning researchers, gaining exposure to the entire workflow from design to deployment. These internships typically provide hands-on experience with tools like FPGA, ASIC simulation environments, or specialized ML hardware platforms, and offer opportunities to contribute to real-world product development and research.

What are popular job titles related to Internship Machine Learning Hardware jobs in Texas?

For Internship Machine Learning Hardware jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Internship Machine Learning Hardware jobs in Texas look for?

The top searched job categories for Internship Machine Learning Hardware jobs in Texas are:

What cities in Texas are hiring for Internship Machine Learning Hardware jobs?

Cities in Texas with the most Internship Machine Learning Hardware job openings:

Internship Machine Learning Hardware jobs near you
Infographic showing various Internship Machine Learning Hardware job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 77% Full Time, 20% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Computer Vision & Machine Learning, Junior

Allen Control Systems

Austin, TX • On-site

Full-time

Re-posted 3 days ago

Job description

Job Summary:
Allen Control Systems (ACS) is a cutting-edge defense startup developing autonomous gun turret technology. The Junior Computer Vision & Machine Learning role focuses on developing and optimizing algorithms for drone detection and classification, collaborating with engineers, and testing systems in various environments.
Responsibilities:
• Development and optimization of computer vision algorithms for our autonomous gun turret, focusing on real-time drone detection, tracking, and classification.
• Design and implement machine learning models that can operate in resource-constrained environments while maintaining high accuracy and reliability.
• Collaborate closely with electrical engineers to integrate computer vision systems into the turret's hardware architecture.
• Conduct extensive testing and validation of computer vision algorithms in various scenarios to ensure robustness and performance under different environmental conditions.
• Contribute to the hardening of the prototype turret into a military-grade system, and assist in developing variants for different weapon systems and engagement ranges.
Qualifications:
Required:
• Deep passion for machine learning, computer vision, and robotics, and have been exploring these areas since early in your career.
• At least a Bachelor's degree in Computer Science, Electrical Engineering, or a related field, with a strong focus on machine learning and computer vision.
• 0-3+ years of experience working on machine-learning-based computer vision, ideally in the context of robotics.
• A proven track record of developing and deploying computer vision systems, ideally in real-time or safety-critical applications.
• Proficient in Python, C++, and have experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
• Experience with embedded systems and integrating computer vision algorithms into hardware.
• Familiar with various sensors (e.g., cameras, LIDAR, RADAR) and their integration into autonomous systems.
• You enjoy collaborating with other engineers to solve complex technical challenges.
Company:
Allen Control Systems develops autonomous defense technologies designed to detect, track, and counter unmanned aerial threats. Founded in 2022, the company is headquartered in Austin, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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