ZipRecruiter

Log In

1

Hourly Embedded Machine Learning Jobs in Washington

Mixpeek

Machine Learning Engineer

Washington, DC · On-site

$180 - $240/hr

  • Medical

  • Retirement

  • PTO

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 ...

New

Adelphi

Machine Learning Engineer

Washington, DC · On-site

$150 - $210/hr

  • Medical

  • Retirement

About the Role The Machine Forward Deployed Learning Engineer position requires a mix of software ... Experience in a customer‑facing or embedded delivery role. * Exposure to federated or ...

Expression

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Develop and deploy standalone and embedded machine learning models supporting mission decision-making, automation, anomaly detection, and pattern recognition. * Select and implement appropriate ...

New

Xometry

Staff Machine Learning Engineer

North Bethesda, MD · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... Xometry's embedded DFM AI + IQE integration with Teamcenter and Designcenter. You will be ... machine learning engineering, with a track record of owning and delivering complex ML systems in ...

Xometry

Staff Machine Learning Engineer

North Bethesda, MD · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... Xometry's embedded DFM AI + IQE integration with Teamcenter and Designcenter. You will be ... machine learning engineering, with a track record of owning and delivering complex ML systems in ...

Expression

Data Engineer

Arlington, VA

$131K - $158K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Develop and deploy standalone and embedded machine learning models supporting mission decision-making, automation, anomaly detection, and pattern recognition. * Select and implement appropriate ...

New

CoStar

Homes.com - Machine Learning Engineer

Arlington, VA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Homes.com - Machine Learning Engineer CoStar Group is a leading global provider of commercial and ... The final salary or hourly rate offered for this role with fall within the range set forth below ...

CoStar Group

Homes.com - Machine Learning Engineer

Arlington, VA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Homes.com - Machine Learning Engineer CoStar Group is a leading global provider of commercial and ... The final salary or hourly rate offered for this role with fall within the range set forth below ...

next page

Showing results 1-20

All JobsHourly Embedded Machine Learning JobsHourly Embedded Machine Learning Jobs in Washington

Hourly Embedded Machine Learning information

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.

What are the most commonly searched types of Embedded Machine Learning jobs in Washington?

The most popular types of Embedded Machine Learning jobs in Washington are:

What are popular job titles related to Hourly Embedded Machine Learning jobs in Washington?

For Hourly Embedded Machine Learning jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Hourly Embedded Machine Learning jobs in Washington look for?

The top searched job categories for Hourly Embedded Machine Learning jobs in Washington are:

What cities in Washington are hiring for Hourly Embedded Machine Learning jobs?

Cities in Washington with the most Hourly Embedded Machine Learning job openings:

Hourly Embedded Machine Learning jobs near you
Infographic showing various Hourly Embedded Machine Learning job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer

Mixpeek

Washington, DC • On-site

$180 - $240/hr

Other

Medical, Retirement, PTO

Posted 3 days ago

New

Job description

About Adelphi

Adelphi's Vision is to build the biggest AI Deployment company for National Security, which requires talent that is extremely good at problem solving, gets excited about National Security challenges, and thrives in software factories. We're executing a Mission that (1) Identifies the core bottlenecks in Warfighting, Intelligence and the Enterprise, (2) Assigns top talent with backgrounds in systems and machine learning engineering, and (3) Finds repeatability in solution development to target similar offices across the DoW/IC. The business has 10x'd in under two years and has built trust with the senior most leaders at the Department of War and Intelligence Community.

About the Role:

The Machine Forward Deployed Learning Engineer position requires a mix of software development, LLM Ops, and SecDevOps practices, resulting in an exciting, fast-paced engineering role. This role requires the ability to contribute to solutions across the full LLM stack, from the OS, storage, and network up to the API and transport layer. Experience in the defense or intelligence fields is required. You will contribute to end-to-end delivery of agentic, full-stack systems built on top of frontier models, from first prototype to stable production, embedded alongside our defense and intelligence customers.

Location:

This role is based in the DC/Metro area; remote candidates will be considered with 25% travel expected.

Clearance Requirement:

An active U.S. Government clearance is strongly preferred, but we are open to clearance eligible candidates.

Is this you?

We are an AI-native engineering team. We expect every engineer to leverage LLMs and AI tooling as a core part of how they design, build, ship, and operate agentic systems that turn frontier-model capability into mission outcomes.

  • You use AI coding tools (Claude Code, Cursor, Copilot) daily and instinctively.

  • You leverage LLMs across the development lifecycle, and stay current with emerging models and tooling.

  • You have working knowledge of modern agent frameworks and SDKs (LangGraph, OpenAI Agents SDK, Claude Agent SDK, AutoGen, or similar).

  • Familiarity with MCP or similar LLM integration frameworks.

  • You have a clear-eyed view of AI limitations. You know when to trust AI-generated output and when to verify.

Expectations:

  • Contribute to end-to-end delivery of agentic, full-stack systems from prototype to production, embedded alongside defense and intelligence customers.

  • Build and deploy ML services leveraging LLMs, embeddings, RAG, and agent orchestration into production environments, including classified and air-gapped ones.

  • Work directly with customers to understand problems, support delivery sequencing, and ship AI applications under real-world constraints.

  • Help codify repeatable patterns into reusable tools and building blocks that help the team ship faster.

Bonus Points:

  • Familiarity with infrastructure management (Docker, Kubernetes, AWS).

  • Exposure to encryption, authentication, Linux systems administration, DevOps, or SRE.

  • Any production experience with agentic services or forward-deployed AI applications.

  • Experience in a customer-facing or embedded delivery role.

  • Exposure to federated or privacy-preserving data architectures.

Benefits:

  • Healthcare coverage: 100% employee premium and 50% dependents premium coverage of a platinum-level plan.

  • 401K with 2% company match.

  • Equity in a seed-stage business.

  • Access to 6713 Club - a members-only club in McLean, VA.

  • $500 monthly Physical and Mental Health reimbursement program.

  • Flexible PTO policy.

  • Competitive salary and equity compensation.

  • Opportunity to work on impactful projects in the national security sector.

  • Career growth and leadership opportunities in a dynamic, innovative environment.

#J-18808-Ljbffr

Apply