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Remote Embedded Machine Learning Jobs in Carteret, NJ

Canals

Machine Learning Engineer

New York, NY · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

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Remote Embedded Machine Learning information

See Carteret, NJ salary details

$71K

$155.6K

$176.5K

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

As of Sep 6, 2026, the average yearly pay for remote embedded machine learning in Carteret, NJ is $155,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,400.00 and $175,500.00 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.

What job categories do people searching Remote Embedded Machine Learning jobs in Carteret, NJ look for?

The top searched job categories for Remote Embedded Machine Learning jobs in Carteret, NJ are:

What cities near Carteret, NJ are hiring for Remote Embedded Machine Learning jobs?

Cities near Carteret, NJ with the most Remote Embedded Machine Learning job openings:

Remote Embedded Machine Learning jobs near you
Infographic showing various Remote Embedded Machine Learning job openings in Carteret, NJ as of June 2026, with employment types broken down into 55% Full Time, 11% Part Time, and 34% Contract. Highlights an 100% Remote job distribution, with an average salary of $155,605 per year, or $74.8 per hour.

Sr Java Engineer // UNICORN Startup // Fully Remote

Motion Recruitment

NY • Remote

$137K - $181K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 5 days ago

Job description


A rapidly growing sleep technology company is seeking a Senior Backend Engineer to join its high-performing engineering organization. This full-time opportunity can be performed remotely and offers the chance to work on a sophisticated technology platform that combines cloud computing, IoT devices, machine learning, and large-scale data processing. The ideal candidate will bring strong backend engineering expertise and experience building distributed systems in cloud-native environments.
This is an opportunity to work on technology that directly impacts the health and performance of users worldwide. Engineers on this team own meaningful projects from design through deployment and collaborate closely with product, mobile, embedded, machine learning, and data teams. The organization values innovation, autonomy, and technical excellence, making it an excellent fit for someone looking to tackle challenging engineering problems while accelerating their career growth.
Required Skills & Experience
  • 8+ years of professional software engineering experience
  • 5+ years focused on backend engineering or site reliability engineering
  • Experience building and supporting distributed systems
  • Cloud platform experience (AWS, Azure, or GCP)
  • Experience with microservices architectures
  • Strong understanding of scalability, reliability, and observability
Desired Skills & Experience
  • Kubernetes experience
  • Infrastructure automation experience
  • Experience supporting IoT or connected device platforms
  • Data pipeline or streaming architecture experience
  • SRE or platform engineering background
  • Machine learning infrastructure exposure
What You Will Be Doing
Tech Breakdown
  • 40% Distributed Systems Development
  • 30% Cloud Infrastructure & Reliability
  • 20% Microservices Architecture
  • 10% Automation & Monitoring

Daily Responsibilities
  • 85% Hands On Engineering
  • 15% Team Collaboration

The Offer
  • Competitive Salary
  • Substantial Equity
You will receive the following benefits:
  • Medical, Dental, and Vision Insurance
  • Flexible PTO
  • Equity Participation
  • Remote Flexibility
  • Employee Product Benefits

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.
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