ZipRecruiter

Log In

2

Remote Embedded Machine Learning Jobs in Massachusetts

GN Group

Machine Learning Engineer - Edge

Lowell, MA · On-site +1

$86K - $135K/yr

Machine Learning Engineer - Edge *Please consider before applying: This is a hybrid role, and ... Experience with embedded systems and hardware platforms. * Fundamentals of audio and speech signal ...

Autodesk

Senior Machine Learning Engineer

Boston, MA · On-site +1

$113K - $155K/yr

This role is currently open to remote work. Candidates must be located near one of our hub ... Design and implement machine learning capabilities that improve Autodesk's customer-facing ...

C the Signs

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

C the Signs

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

ASUS

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

ASUS Robotics & AI Center Senior Machine Learning Engineer The ASUS Robotics & AI Center is seeking ... Optimize models for real-time performance on embedded and edge computing platforms. * Build and ...

ASUS

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global ... Optimize models for real-time performance on embedded and edge computing platforms. * Build and ...

next page

Showing results 1-20

All JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in Massachusetts

Remote Embedded Machine Learning information

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.
What are the most commonly searched types of Embedded Machine Learning jobs in Massachusetts? The most popular types of Embedded Machine Learning jobs in Massachusetts are:
What are popular job titles related to Remote Embedded Machine Learning jobs in Massachusetts? For Remote Embedded Machine Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Remote Embedded Machine Learning jobs in Massachusetts look for? The top searched job categories for Remote Embedded Machine Learning jobs in Massachusetts are:
What cities in Massachusetts are hiring for Remote Embedded Machine Learning jobs? Cities in Massachusetts with the most Remote Embedded Machine Learning job openings:
Remote Embedded Machine Learning jobs near you
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