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Embedded Machine Learning Internship Jobs in South Carolina

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

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Embedded Machine Learning Internship information

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.
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Embedded Machine Learning Internship jobs near you

Machine Learning Engineer II

Techtronic Industries - TTI

Anderson, SC • On-site

Full-time

Re-posted yesterday

Techtronic Industries TTI rating

8.2

Company rating: 8.2 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

130th of 487 rated machine equipment manufacturers

Job description

Job Summary:
Techtronic Industries is a fast-growing world leader in Power Tools and Accessories, seeking an Electrical Machine Learning Engineer II to join their team. The role involves identifying and developing ML-enabled features for outdoor power tools, collaborating with cross-functional teams to create data-driven solutions.
Responsibilities:
• Identify, develop, and validate ML-enabled features for outdoor power tools within the OP EE organization.
• Frame ML use cases, design data-collection strategies and ground-truth methods.
• Perform data engineering and feature development, train and tune models in Python, and execute validation to characterize accuracy, robustness, and corner cases.
• Establish and improve team workflows and guidelines covering the end-to-end ML lifecycle—from problem definition through model training, validation, and deployment considerations.
Qualifications:
Required:
• Bachelor of Science degree in Computer Science, Computer Engineering, Electrical Engineering, or a related scientific/engineering discipline with completed coursework, certification, or specialization in Machine Learning, Data Science, or a closely related area.
• Minimum 2 years of hands-on experience applying ML in an applied setting (e.g., embedded/edge, signal processing, sensing, or electromechanical products), including data collection and model validation.
• Demonstrated experience applying fundamental ML approaches (e.g., supervised learning for classification/regression, feature engineering, model selection, and hyperparameter tuning).
• Proficient in developing, debugging, and validating Python code, with experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.).
• Experience with modern software development practices and tools (Git-based workflows; familiarity with CI/CD and containers is a plus).
• Ability to develop and debug code in an embedded environment (C/C++ preferred), including bring-up and hardware-facing troubleshooting will be a plus.
• Basic knowledge of sensor technologies (e.g., IMUs, thermistors/temperature sensing, magnetic/optical sensing) and microcontroller interfacing.
• Strong problem-solving and system-thinking skills, with the ability to work in a fast-paced, prototype-to-demo environment.
• Strong technical communication skills and the ability to plan/execute work to meet project schedules.
• Demonstrated ownership of deliverables, including understanding dependencies and collaborating effectively with cross-functional stakeholders.
Company:
Techtronic Industries Company Limited (“TTI”, or the “Company”), founded in 1985 by German entrepreneur Horst Julius Pudwill, is a world leader in cordless technology. Founded in 1985, the company is headquartered in Kwai Tsing, HKG, with a team of 10001+ employees. The company is currently Late Stage.

What Techtronic Industries TTI employees say

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