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Remote Embedded Machine Learning Jobs in Westfield, MA

micro1 AI

AI Trainer - Microbiology Expert

Hartford, CT · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Kemper

SVP, Chief Technology Officer (CTO)

Hartford, CT · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... IL, Remote-MI, Remote-NJ, St. Louis, Missouri Details Kemper is one of the nation's leading ... Lead enterprise implementation of Generative AI, Machine Learning, Intelligent Automation, and ...

The Hartford

AVP Applied AI

Hartford, CT · On-site +1

The Assistant Vice President (AVP), Applied AI leads data science, traditional machine learning ... This role can have a Hybrid or Remote work schedule. Candidates who live near one of our office ...

iSoftStone

Sr. Project Manager (Infrastructure)

Manchester, CT · Remote

$65 - $75/hr

  • Medical

  • Dental

  • Vision

  • Retirement

Remote Opportunity in the Tri-State Area (NY, NJ or CT) Applicants must be legally authorized to ... machine learning and AI. With 20 delivery centers and more than 90,000 employees worldwide ...

All JobsEmbedded Machine Learning JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in Westfield, MA

Remote Embedded Machine Learning information

See Westfield, MA salary details

$73.1K

$160.2K

$181.7K

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

As of Aug 18, 2026, the average yearly pay for remote embedded machine learning in Westfield, MA is $160,157.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,300.00 and $180,600.00 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.

Remote Embedded Machine Learning jobs near you

Machine learning Solution Architect: Remote Role

Qualis1 Inc

Hartford, CT • Remote

$64.50 - $85/hr

Contractor

Re-posted 5 days ago

Job description

Role: AI/ Machine learning Architect

Location: Hartford, CT, remote

Duration: 6+ months

Description:

Need Machine learning Architect with Azure cloud