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Remote Embedded Machine Learning Jobs in Carteret, NJ

Moody's Analytics

MLOps Engineer

New York, NY · On-site +1

We have a flexible work environment and allow remote work depending on one's personal choice. Responsibilities: As the Machine Learning Ops Engineer for the AI Team you will: * Work closely with the ...

C the Signs

AI Data Engineer

New York, NY · On-site +1

$125K - $150K/yr

Collaborate with data scientists and machine learning engineers to understand data requirements for ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

C the Signs

AI Data Engineer

New York, NY · Remote

$117K - $140K/yr

Collaborate with data scientists and machine learning engineers to understand data requirements for ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

Mercor

ML Engineer - AI Coding Expert

New York, NY · Remote

$85/hr

Remote Role Responsibilities * Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks. * Review model-generated implementations involving model ...

Mercor

ML Engineer - Coding Agent Expert

New York, NY · Remote

$85/hr

Remote Role Responsibilities * Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks. * Review model-generated implementations involving model ...

YO AI Labs

Senior Software Engineer - Remote

New York, NY · Remote

$134K - $176K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Moody's Analytics

Senior DevOps Engineer (Remote)

New York, NY · Remote

$142K - $182K/yr

Deployment and productionisation or machine learning model applications in production. * Design and develop reusable Terraform and Ansible modules. * Lead the team in various aspects around stability ...

LEO&Co

Part Time Data Analyst (Remote)

New York, NY · Remote

A real estate services firm in New York City has a great Remote opportunity awaiting a new Data ... Machine Learning or Statistical Analysis, Data Engineering and Data Visualization related work

TSMG

AI/ML Data Contributor

New York, NY · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

TSMG

AI/ML Data Contributor

New York, NY · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

Mercor

ML Research Scientist - PhD

New York, NY · Remote

$110 - $145/hr

Remote Role Responsibilities * Evaluate the accuracy and depth of AI-generated content to strengthen reasoning and rigor in model outputs . * Review complex machine learning research for alignment ...

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All JobsEmbedded Machine Learning JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in Carteret, NJ

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 Aug 16, 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 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 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 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.

MLOps Engineer

Moody's Analytics

New York, NY • On-site, Remote

Full-time

Re-posted 5 days ago

Job description

In the Predictive Analytics AI group, we build data-driven, highly distributed machine learning systems. Our engineers and researchers are responsible for architecting and developing these ML services end-to-end overcoming unique challenges that involve building systems that have high throughput availability, consistency, and low latency. The Predictive Analytics AI Group is the central group in Moody's Analytics comprising of researchers and engineers working together to build data-driven customer-facing products, as well as the necessary infrastructure to support the ML services following the industry leading practices. The group has worked on and built some award-winning AI products like Compliance Catalyst, Adverse Media Monitoring, Coronapulse, Quiqspread, News Edge 2.0, ESG and has participated in various internal automation initiatives. The group also regularly publish and present their work in top-tier academic and industry conferences. We have a flexible work environment and allow remote work depending on one's personal choice.


Responsibilities:

As the Machine Learning Ops Engineer for the AI Team you will:

  • Work closely with the Data Science team and the Data Engineers and DevOps teams in order to deploy machine learning models. Specifically execute continuous integration and continuous delivery (CI/CD) activities to release ML code and ML pipelines into a Production environment
  • Maintain the Machine Learning pipeline and make sure everything is running accurately and reliably
  • Liaise with senior stakeholders across the Data function and the wider business
  • Use industry best practices such as code reviews, pull requests, and peer testing to ensure high quality AI/ML deliverables
  • Build AI/ML model performance benchmarking, evaluation, monitoring capabilities and facilitates resolution of issues with the appropriate teams

SKILLS AND EXPERIENCE


Must Have:

  • Proven industry/commercial/research lab experience (2+ years) deploying machine learning models and maintaining ML pipelines, orchestration, deployment, monitoring, & support
  • Experience creating and maintaining deployment pipelines with CI/CD tools (2+ years)
  • Knowledge of cloud technologies (e.g. AWS) and Extensive Programming experience in Python & SQL
  • Experience in containerization and orchestration (such as Docker, Kubernetes)
  • Practical Knowledge of Machine Learning models in commercial settings
  • Good communication skills

Nice to Have:

  • Experience building batch and/or real-time data & ML pipelines
  • Familiarity with MLflow (or similar platforms like Kubeflow and other tools)
  • Promotes a practice of unifying system development (Dev) and system operations (Ops)

Employment Type: FULL_TIME

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