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Temporary Embedded Machine Learning Jobs (NOW HIRING)

The Director of Machine Learning will define the ML strategy, lead the computer vision organization ... embedded inference) • Familiarity with warehouse, logistics, or supply chain domain • ...

Stay current with the latest machine learning research for wireless and embedded systems, applying ingenuity and a deep understanding of the problems at hand Required Skills * 4+ years experience as ...

Staff Embedded ML Engineer, Edge AI

Boston, MA · On-site

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

Staff Embedded ML Engineer, Edge AI

Boston, MA · On-site

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

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 ...

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 ...

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 ...

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Temporary Embedded Machine Learning information

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$70K

$153.4K

$174K

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

As of Aug 23, 2026, the average yearly pay for temporary embedded machine learning in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is the difference between Temporary Embedded Machine Learning vs Embedded Software Engineer?

AspectTemporary Embedded Machine LearningEmbedded Software Engineer
CredentialsRelevant degrees in CS, EE, or data science; certifications in ML or embedded systemsDegrees in CS, EE; certifications in embedded systems or software development
Work EnvironmentProject-based, often in tech or manufacturing industries, with focus on ML integrationDesigning, developing, and testing embedded software in various industries like automotive, IoT
Industry UsageUsed in AI-driven embedded systems, IoT devices, and smart gadgetsUsed in consumer electronics, automotive, industrial automation

Temporary Embedded Machine Learning specialists focus on integrating machine learning models into embedded devices, often on a project basis. Embedded Software Engineers develop and maintain the software that runs directly on hardware. While both roles require embedded systems knowledge, the ML role emphasizes AI integration, whereas the embedded software engineer focuses on software development and system stability.

What cities are hiring for Temporary Embedded Machine Learning jobs?

Cities with the most Temporary Embedded Machine Learning job openings:

What are the most commonly searched types of Embedded Machine Learning jobs?

The most popular types of Embedded Machine Learning jobs are:

What states have the most Temporary Embedded Machine Learning jobs?

States with the most job openings for Temporary Embedded Machine Learning jobs include:

Director of Machine Learning

Gather AI

Remote

Full-time

Re-posted 7 days ago


Job description

Job Summary:
Gather AI is pioneering a new era of warehouse intelligence through their vision-powered platform that utilizes autonomous drones to capture real-time data. The Director of Machine Learning will define the ML strategy, lead the computer vision organization, and enhance ML capabilities to drive the company's warehouse intelligence 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.