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Internship Machine Learning Hardware Jobs (NOW HIRING)

Jane Street

Machine Learning Engineer

New York, NY

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

The Machine Learning Platform Technology team is building groundbreaking technology for search ... from our hardware. As part of this group, you will work with one of the most exciting high ...

Sanics Edu

What you'll do About the internship Stripe's Applied ML, Data Science, Risk, and Payments organizations are excited to offer PhD machine learning engineering internships for the summer of 2026. This ...

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

As of Sep 11, 2026, the average yearly pay for internship machine learning hardware in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

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 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 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 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.

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Internship Machine Learning Hardware jobs near you
Infographic showing various Internship Machine Learning Hardware job openings in the United States as of September 2026, with employment types broken down into 50% Internship, 25% Full Time, and 25% Part Time. Highlights an 100% In-person job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Internship - PhD: 2027

Bala Cynwyd, PA • On-site

Susquehanna
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Posted 16 days ago

Job description

Overview

Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.

As a Machine Learning Intern at Susquehanna, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You'll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.

What You Can Expect

  • Conduct research and develop ML models to identify patterns in noisy, non-stationary data
  • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • One-on-one mentorship from experienced researchers and technologists
  • Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for

  • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
  • Proven experience applying machine learning techniques in a professional or academic setting
  • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
  • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow
  • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?

  • Work with a world-class team of researchers and technologists
  • Access to unparalleled financial data and computing resources
  • Opportunity to make a direct impact on trading performance
  • Collaborative, intellectually stimulating environment with global reach

About Susquehanna

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.

If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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