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Embedded Machine Learning Internship Jobs in Pittsburgh, PA

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site

They are seeking a Director of Machine Learning to define the ML strategy, lead the computer vision ... embedded inference) • Familiarity with warehouse, logistics, or supply chain domain • ...

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site +1

About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of ... Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference) * Familiarity with ...

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site

About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of ... Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference) * Familiarity with ...

HELLBENDER Inc.

Perception Engineer

Pittsburgh, PA · Hybrid

Experience deploying machine learning models on embedded platforms, such as NVIDIA Jetson or Hailo TPUs, is highly preferred Job Type: Full-time Benefits: * 401(k) * 5% Safe Harbor Contribution to ...

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Embedded Machine Learning Internship information

See Pittsburgh, PA salary details

$24.8K

$41.3K

$85.4K

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

As of Aug 6, 2026, the average yearly pay for embedded machine learning internship in Pittsburgh, PA is $41,341.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,600.00 and $44,700.00 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.
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Embedded Machine Learning Internship jobs near you

Director of Machine Learning

Gather AI

Pittsburgh, PA • On-site

Full-time

Re-posted 6 days ago

Job description

Job Summary:
Gather AI is pioneering a new era of warehouse intelligence with innovative software that utilizes autonomous drones for real-time data capture. They are seeking a Director of Machine Learning to define the ML strategy, lead the computer vision organization, and enhance the company's ML capabilities to support their vision-powered platform.
Responsibilities:
• Define and own the ML strategy and technical roadmap for Gather AI, aligned with product and business objectives
• Lead and grow the Machine Learning and FPT teams, establishing a culture of rigor, experimentation, and production-quality delivery
• Drive improvements to core computer vision models (object detection, segmentation, OCR) used across our drone and MHE Vision products
• Build out MLOps infrastructure — model training pipelines, deployment, monitoring, and CI/CD for ML workloads
• Collaborate with the Director of Cloud Engineering and Director of Autonomy to ensure ML systems integrate seamlessly into the broader platform
• Partner with Product and Operations to translate customer needs into ML-driven product capabilities
Qualifications:
Required:
• 10+ years building and scaling production ML or computer vision systems
• 5+ years managing and growing ML engineering teams
• Deep expertise in computer vision: object detection, image segmentation, OCR, and CNN architectures
• Strong Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to production at scale
• MS or PhD in Computer Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree)
Preferred:
• Experience with drone, robotics, or autonomous systems perception
• Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference)
• Familiarity with warehouse, logistics, or supply chain domain
• Experience with AWS or GCP ML services (SageMaker, Vertex AI)
Company:
We deliver the foundational intelligence layer for the intralogistics industry. Founded in 2017, the company is headquartered in Pittsburgh, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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