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Remote Embedded Machine Learning Jobs (NOW HIRING)

This is a fully remote position, allowing you to work from home or location of record within the U ... Our machine learning engineering team is responsible for developing infrastructure and tooling to ...

This role is fully remote within the US** What You'll Do * Build and scale machine-learning driven features across multiple products * Design reusable architecture that powers and accelerates machine ...

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

This role is fully remote within the US** What You'll Do * Build and scale machine-learning driven features across multiple products * Design reusable architecture that powers and accelerates machine ...

Senior Machine Learning Engineer

New York, NY · On-site +1

$114K - $157K/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 ...

Senior Machine Learning Engineer

California, MD · On-site +1

$100K - $137K/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 ...

$86K - $119K/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 ...

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Remote Embedded Machine Learning information

See salary details

$70K

$153.4K

$174K

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

As of Jul 10, 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:
Infographic showing various Remote Embedded Machine Learning job openings in the United States as of July 2026, with employment types broken down into 43% Full Time, 14% Part Time, and 43% Contract. Highlights an 100% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
Machine Learning Ops Engineer

$54 - $74/hr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Job Title:- Machine Learning Ops Engineer
Duration:- 8+ months
Location:- Remote
Description
  • Proven expertise in machine learning model lifecycleProven expertise and experience in creating data pipelines using Python or R required for real-time model inferenceProven expertise and experience in creating a microservice using Flask or FastAPI or R equivalent for a machine learning model.
  • Experience with APIGEE is a must. Proven experience with Linux bash scripting, Python scripting, or Groovy scripting Proven experience with Docker, and KubernetesProven experience with MPP databases like Teradata and reasonable experience with Hadoop ecosystem products like Hive, HDFS, HBASE, etc.
  • Proven experience with streaming technologies like KafkaProven experience with CICD tools like Jenkins, Shell Scripting, Gitlab, Github, Gitlab Pages, and Gitlab Documentation Proven experience with logging, alerting, debugging, and monitoring tools like ELK, Kibana, Catchpoint, Prometheus, and Splunk. Experience with EKS, or GKE is a plus