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Hourly Embedded Machine Learning Jobs (NOW HIRING)

MatrixSpace

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

Experience with embedded systems, GPUs, NPUs, FPGAs, or hardware acceleration. * Familiarity withMLOps, CI/CD, model monitoring, and large-scale production systems. At MatrixSpace, Machine Learning ...

Mixpeek

Machine Learning Engineer

Washington, DC · On-site

The Machine Forward Deployed Learning Engineer position requires a mix of software development, LLM ... Experience in a customer-facing or embedded delivery role. * Exposure to federated or privacy ...

Liquid XR

Machine Learning Engineer

Los Angeles, CA · On-site +1

The Role We are seeking a Machine Learning Engineer to develop advanced models for extracting ... Exposure to embedded or edge deployment constraints * Background in applied domains involving ...

SimpliSafe

Staff Embedded ML Engineer, Edge AI

Boston, MA

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

SimpliSafe

Staff Embedded ML Engineer, Edge AI

Boston, MA · On-site

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

SimpliSafe

Staff Embedded ML Engineer, Edge AI

Boston, MA · On-site

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site

They are seeking a Director of Machine Learning to define the ML strategy, lead the computer vision ... embedded inference) • Familiarity with warehouse, logistics, or supply chain domain • ...

Motorola

Machine Learning Engineer

Los Angeles, CA · On-site

$150K - $180K/yr

Stay current with the latest machine learning research for wireless and embedded systems, applying ingenuity and a deep understanding of the problems at hand Required Skills * 4+ years experience as ...

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Hourly Embedded Machine Learning information

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$70K

$153.4K

$174K

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

As of Sep 10, 2026, the average yearly pay for hourly 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 is an hourly embedded machine learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

How does an hourly embedded machine learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What are the key skills and qualifications needed to thrive as an hourly embedded machine learning engineer, and why are they important?

To thrive as an Hourly 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 engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

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Hourly Embedded Machine Learning jobs near you
Infographic showing various Hourly Embedded Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.

Machine Learning Engineer

Los Angeles, CA • On-site

Ascent Developer Solutions
See more jobs at Ascent Developer Solutionsexternal

Full-time

Re-posted 8 days ago

Job description

ROLE SUMMARY 

The Machine Learning Engineer is a major contributor in driving our company's innovation and data-driven decision-making. By harnessing advanced analytics, machine learning, and big data technologies, this role directly impacts strategic business outcomes, revealing actionable insights and predicting trends that shape the future of our operations. Embedded at the intersection of data and strategy, the Data Scientist empowers the organization to navigate complex challenges, optimize performance, and unlock new growth opportunities. 

ESSENTIAL DUTIES 

Data and analysis 

  • Analyze public records and other real estate data using NLP and machine learning techniques to identify patterns and cluster entities. 
  • Develop methods for evaluating and selecting large language models (LLMs) for deployment. 
  • Build predictive models to identify potential borrowers, likelihood of default, and quality/valuations of properties for lending activities. 
  • Identify new business opportunities through tracking competitor trends and keeping management aware of developer lending market trends and insights. 
  • Assist in fostering a culture of test & learn within the company. 

Leadership  

  • Serve as analytics consultant to a broad variety of line-of-business teams. 
  • Partner with technology teams on product changes and impacts on data/performance. 
  • Mentor junior analysts on various data science techniques. 

 QUALIFICATIONS 

  • Bachelor's degree in quantitative field. 
  • 5-7 years of experience in analytical or consulting roles. 
  • Strong data science skills with AI/ML related Python libraries such as PyTorch, TensorFlow, and Keras. Conceptual knowledge of LLM's. 
  • Strong knowledge of statistics, hypothesis testing, and setting up experiments. 
  • Must have deployed several models to production. 
  • Exposure to data engineering skills. 
  • Strong communication and partnership skills, effective cross-department collaboration skills. 
  • Self-starter who can work under limited supervision. 
  • Mentoring skills to help develop junior analysts. 

WORK ENVIRONMENT 

  • This role works on-site from Ascent's Encino office 2 days per week 

THE PAY 

Salary range is $130,000-$150,000 per year, with a discretionary bonus of 20% per year. 

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