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Remote Embedded Machine Learning Jobs (NOW HIRING)

Wings of Destiny

Machine Learning Engineer

Malibu, CA · Remote

Remote Commitment: 5-10 hours per week (flexible) Duration: 3-6 months (with potential extension ... Role Overview We are seeking a Machine Learning Engineer (Volunteer) to help design, build, and ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Fully remote, U.S.-based * Health Benefits : Comprehensive health, dental, and vision coverage Time ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

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

Alignerr

Machine Learning Engineer

Manhattan, NY · Remote

$154K/yr

Machine Learning Engineer (AI Data Trainer) About the Role What if your machine learning expertise ... Remote * Commitment : 10-40 hours/week What You'll Do * Construct precise, well-structured ...

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 ...

nou Systems

Machine Learning Engineer

Colorado Springs, CO · On-site +1

$100K - $160K/yr

Work in Linux-based, containerized development environments using VS Code Dev Containers, Remote ... in machine learning, data science, or backend software development. * Hands-on experience ...

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 ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

DocuSign

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Employee divides their time between in-office and remote work. Access to an office location is ...

DocuSign

Machine Learning Engineer

Seattle, WA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Employee divides their time between in-office and remote work. Access to an office location is ...

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Remote Embedded Machine Learning information

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$174K

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

As of Jun 19, 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 are the key skills and qualifications needed to thrive as a Remote Embedded Machine Learning Engineer, and why are they important?

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 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 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.

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.
More about Remote Embedded Machine Learning jobs
What cities are hiring for Remote Embedded Machine Learning jobs? Cities with the most Remote 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 Remote Embedded Machine Learning jobs? States with the most job openings for Remote Embedded Machine Learning jobs include:
What job categories do people searching Remote Embedded Machine Learning jobs look for? The top searched job categories for Remote Embedded Machine Learning jobs are:
Remote Embedded Machine Learning jobs near you
Infographic showing various Remote Embedded Machine Learning job openings in the United States as of June 2026, with employment types broken down into 75% Full Time, 17% Part Time, and 8% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
Senior Embedded Software Engineer

Senior Embedded Software Engineer

Motional

Boston, MA • On-site, Remote

$134K - $176K/yr

Other

Posted 13 days ago

Job description

Mission Summary:

Motional's onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional's next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional's current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

  • Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.
  • Design test harnesses for embedded software components and full systems
  • Provide technical mentorship to engineers.
  • Proactively work with cross-functional engineering teams to solve complex and interesting problems.

What We're Looking For:

  • Experience with creating detailed requirements from use cases.
  • Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
  • Experience writing software for embedded platforms in C and C++.
  • Experience with Test-Driven Development (TDD).
  • Experience working on embedded Linux / RTOSs.
  • Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
  • Experience with debugging on embedded platforms.
  • Experience writing software in Python and experience doing automation with shell scripting.
  • Experience working with ARM Cortex MCUs or Microprocessors.

Bonus Points (not required):

  • Experience working with large data pipelines, and platforms that require deterministic execution.
  • Experience using inter-system communication protocols such as I2C and SPI
  • Experience deploying Machine Learning models.
  • Experience working with GPUs.
  • Experience working directly with the Linux kernel or Device Drivers.
  • Experience with Simulation and Code Generation, and knowing when their use is appropriate.
  • Experience working with Bazel.
  • Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
  • Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Apply