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Hourly Embedded Machine Learning Jobs in Washington

Parsons

Machine Learning / Data Scientist

Washington, DC · On-site

$88K - $154K/yr

The Machine Learning / Data Scientist is a hands-on practitioner with strong capabilities in model ... Familiarity with integrating model outputs into BI tools or applications (e.g., via APIs, embedded ...

Bespoke Technologies, Inc

R&D Computer Engineer

Washington, DC · On-site

$126K - $148K/yr

This role offers a unique opportunity to gain hands-on research experience at the intersection of embedded systems, machine learning, and audio technologies. The successful engineer will contribute ...

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Hourly Embedded Machine Learning information

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.

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 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.

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 July 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Machine Learning / Data Scientist

Parsons

Washington, DC • On-site

$88K - $154K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 25 days ago

Parsons rating

7.9

Company rating: 7.9 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

218th of 443 rated engineering

Job description

In a world of possibilities, pursue one with endless opportunities. Imagine Next!At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what's possible.

Job Description:

We have a career opportunity for a Machine Learning / Data Scientist to develop advanced analytical models and experiments that enhance decision-making, improve forecasting, and uncover insights across mission and support activities. This role would be based in Washington, DC. Would be required to be on-site

This role will support the enablement of machine learning capabilities within our analytics environment, working closely with data analysts, engineers, and program stakeholders.

The Machine Learning / Data Scientist is a hands-on practitioner with strong capabilities in model development, data preparation, and analytical storytelling. This role requires the ability to frame complex problems, select appropriate modeling approaches, implement and validate models, and communicate results in accessible terms to non-technical audiences.

Key Responsibilities:

  • Design and implement machine learning and advanced analytics solutions that address operational, programmatic, or strategic questions.
  • Collaborate with stakeholders to define analytical problems, identify relevant data, and translate business needs into modeling requirements.
  • Prepare and engineer features from multiple data sources, ensuring data quality and suitability for modeling.
  • Develop, train, and validate models (e.g., classification, regression, clustering, forecasting) using appropriate techniques and tools.
  • Evaluate model performance, perform error analysis, and refine approaches to improve accuracy, robustness, and interpretability.
  • Integrate model outputs into dashboards, applications, or automated workflows, in coordination with analytics and development teams.
  • Document modeling approaches, assumptions, and results, and communicate findings through clear narratives and visualizations.
  • Support experimentation and pilot projects that explore new analytical techniques and tools.
  • Contribute to the development of standards and practices for responsible and sustainable use of advanced analytics.

Typical Assignments:

  • Building predictive or prescriptive models that support prioritization of projects, resource allocation, or risk assessment.
  • Conducting exploratory data analysis to identify patterns, anomalies, and opportunities for improved performance.
  • Developing prototypes of ML-enabled features that can be integrated into existing dashboards or applications.
  • Supporting performance management by providing advanced analyses of trends and drivers underlying key metrics.
  • Collaborating with data management staff to ensure datasets are suitable for modeling and reproducible analysis.
  • Preparing technical and non-technical presentations that summarize modeling methods, findings, and implications.

Education and Experience:

  • Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a closely related field; a master's degree is preferred but not required, or equivalent work experience.
  • 5+ years of experience in data science, machine learning, or advanced analytics roles.
  • Demonstrated experience developing, validating, and deploying machine learning models using tools such as Python, R, or equivalent.
  • Strong background in statistics, model evaluation, and experimental design.
  • Experience with data preparation, feature engineering, and working with complex, multi-source datasets.
  • Familiarity with integrating model outputs into BI tools or applications (e.g., via APIs, embedded analytics) is preferred.
  • Experience working within mission-oriented or public sector environments (e.g., DHS, DoD) is a plus.

Security Clearance Requirement:

NoneThis position is part of our Critical Infrastructure team.For more than 80 years, our experts have designed and delivered the critical infrastructure that connects and protects communities around the world. We work in collaborative teams, both within the company and with our partners and customers, to plan, design, build, and modernize infrastructure. We take special pride in projects and solutions that improve communities as well as people's quality of life by promoting economic growth, enhancing mobility, and increasing sustainability and resiliency. Powered by our people, we provide the imagination necessary to support our customers' visions-and to help them see what's next!Salary Range: $88,400.00 - $154,700.00We value our employees and want our employees to take care of their overall wellbeing, which is why we offer best-in-class benefits such as medical, dental, vision, paid time off, Employee Stock Ownership Plan (ESOP), 401(k), life insurance, flexible work schedules, and holidays to fit your busy lifestyle!Parsons is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, veteran status or any other protected status.We truly invest and care about our employee's wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest-APPLY TODAY!

Parsons is aware of fraudulent recruitment practices. To learn more about recruitment fraud and how to report it, please refer tohttps://www.parsons.com/fraudulent-recruitment/.

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