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Remote Embedded Machine Learning Jobs (NOW HIRING)

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 ...

Syngenta

Machine Learning Engineer

NC · Remote

This is an opportunity to apply cutting-edge remote sensing and AI technologies to solve real-world ... Contribute across the full lifecycle of machine learning projects, including problem definition ...

Syngenta Seeds

Machine Learning Engineer

NC · Remote

This is an opportunity to apply cutting-edge remote sensing and AI technologies to solve real-world ... Contribute across the full lifecycle of machine learning projects, including problem definition ...

Gather AI

Principal Machine Learning Scientist

Explore next-generation perception capabilities, including embedded and on-prem inference optimization for new deployment targets What You'll Need * 10+ years of experience in machine learning or ...

Apex Informatics

Machine Learning Engineer

Remote We are seeking an Applied Machine Learning Engineer with a strong focus on practical solutions and software development (ability to work on both open-ended research problems and production ...

Thorn

Staff Machine Learning Engineer

... is deeply embedded within our core-a shared code that drives us to do challenging work with ... You'll collaborate with a diverse group of peers in a remote environment centered on wellness, care ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Thorn

Senior Machine Learning Engineer

$125K - $165K/yr

... is deeply embedded within our core-a shared code that drives us to do challenging work with ... You'll collaborate with a diverse group of peers in a remote environment centered on wellness, care ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · Remote

$126K - $180K/yr

... devices/embedded systems. * White-box understanding of classical ML algorithms (SVMs, HMMs ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Weekday AI

Machine Learning & NLP Expert

$80 - $110/hr

This is a part-time, fully remote opportunity requiring approximately 20 hours per week . Requirements Key Responsibilities * Design challenging, real-world machine learning and natural language ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

... devices/embedded systems. * White-box understanding of classical ML algorithms (SVMs, HMMs ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

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Remote Embedded Machine Learning information

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$70K

$153.4K

$174K

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

As of Sep 9, 2026, the average yearly pay for remote 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 a remote embedded machine learning engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What are the key skills and qualifications needed to thrive as a remote embedded machine learning engineer?

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What are some common challenges faced by remote embedded machine learning engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

More about Remote Embedded Machine Learning jobs

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What other helpful pages are available for Remote Embedded Machine Learning?

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Remote Embedded Machine Learning jobs near you
Infographic showing various Remote Embedded Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.

Director of Machine Learning

Pittsburgh, PA • On-site, Remote

Gather AI
Industrial Automation Equipment Manufacturing • 11 - 50 employees
Learn more about Gather AIexternal

Full-time

Re-posted 9 days ago

Job description

About Us
Are you ready to build the future of supply chain? At Gather AI, we're not just creating software; we're pioneering a new era of warehouse intelligence. We've developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining "on-time, in full" delivery.
If you're looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We're leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.
About the Team
You'll lead the Machine Learning and FPT teams, working closely with the Director of Cloud Engineering and Director of Autonomy. Cross-departmentally, you'll collaborate with Product and Business leadership to translate ML capabilities into product value. This is a high-visibility role with a direct line to executive leadership and significant influence over product direction.
About the Role
We are looking for a Director of Machine Learning to define our ML strategy, lead our computer vision organization, and drive the next phase of ML maturity at Gather AI. You will assess existing ML and CV capabilities, identify gaps and opportunities, and establish a clear technical vision for how machine learning will power our warehouse intelligence platform over the next 12-18 months.
The ideal candidate brings deep computer vision expertise, a track record of shipping production ML systems, and the leadership experience to build and scale a world-class ML team.
What You'll Do
  • 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

What You'll Need
  • 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)

Nice to Have
  • 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)

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