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Remote Embedded Machine Learning Jobs in Virginia

Booz Allen Hamilton, Inc.

AI/ML Engineer, Lead

Ashburn, VA · On-site +1

$104K - $138K/yr

As an AI/Machine Learning Engineer, you'll lead the design, development, and deployment of advanced ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

Comcast

Engineer 6, Machine Learning, Data & AI

Reston, VA · On-site +1

$119K - $143K/yr

... remote option.) Job Summary We are seeking a visionary Senior Technologist, Data & Agentic AI ... Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives.

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Node.Digital

Senior AI/ML Engineer

Herndon, VA · On-site +1

$107K - $147K/yr

You will focus on building generative AI applications with embedded artifcial intelligence or machine learning in support of continuous improvement, learning and augmented decision-making. Key ...

Maximus

Data Scientist (Remote)

VA · On-site +1

General information Job Posting Title Data Scientist (Remote) Date Tuesday, August 4, 2026 City ... NLP, and machine learning (both supervised and unsupervised) to improve relevance and ...

1872 Consulting

NLP Developer

Herndon, VA · On-site +1

Desired Skills:8+ years of hands-on experience as a machine learning engineer or data scientist.Ph.D./Master's degree in the previously mentioned fields.Experience working with remote sensing data ...

1872 Consulting

NLP Developer

Herndon, VA · On-site +1

Desired Skills:8+ years of hands-on experience as a machine learning engineer or data scientist.Ph.D./Master's degree in the previously mentioned fields.Experience working with remote sensing data ...

ASSYST, Inc.

Software Developer

Sterling, VA · Remote

Develop prototypes and systems leveraging AI and Machine Learning for client projects and internal ... Remote work is not permitted. ASSYST Benefits: We are proud to offer a robust benefits package ...

ASSYST, Inc.

Software Developer

Sterling, VA · Remote

Develop prototypes and systems leveraging AI and Machine Learning for client projects and internal ... Remote work is not permitted. ASSYST Benefits: We are proud to offer a robust benefits package ...

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All JobsEmbedded Machine Learning JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in Virginia

Remote Embedded Machine Learning information

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 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 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 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 the most commonly searched types of Embedded Machine Learning jobs in Virginia?

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

What are popular job titles related to Remote Embedded Machine Learning jobs in Virginia?

For Remote Embedded Machine Learning jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Remote Embedded Machine Learning jobs in Virginia look for?

The top searched job categories for Remote Embedded Machine Learning jobs in Virginia are:

What cities in Virginia are hiring for Remote Embedded Machine Learning jobs?

Cities in Virginia with the most Remote Embedded Machine Learning job openings:

Remote Embedded Machine Learning jobs near you

AI/ML Engineer, Lead

Booz Allen Hamilton, Inc.

Ashburn, VA • On-site, Remote

$104K - $138K/yr

Full-time, Part-time

Medical, Life, Retirement, PTO

Posted 10 days ago

Booz Allen Hamilton rating

8.9

Company rating: 8.9 out of 10

Based on 49 frontline employees who took The Breakroom Quiz

10th of 72 rated business consultants

Job description


Remote Work:
Hybrid
Job Number:
R0246710
Location:
Ashburn,VA,US
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AI/ML Engineer, Lead
The Opportunity:
As an AI/Machine Learning Engineer, you'll lead the design, development, and deployment of advanced AI and ML systems that support enterprise products and strategic initiatives. This role combines deep technical expertise with the ability to collaborate across engineering, product, and data teams. The ideal candidate has extensive experience building production-grade ML models, optimizing model performance, and guiding architectural decisions around scalable AI systems. As an experienced engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using ML techniques makes you an integral part of delivering a customer-focused solution.
What You'll Do:
  • Design, develop, and deploy machine learning models and AI systems for large-scale production environments.
  • Lead end-to-end ML lifecycle processes including data exploration, feature engineering, experimentation, model training, evaluation, and deployment.
  • Architect scalable ML pipelines and infrastructure using modern frameworks and cloud technologies.
  • Collaborate with cross-functional stakeholders to translate business requirements into ML-driven solutions.
  • Mentor junior engineers and contribute to best practices, coding standards, and technical excellence.
  • Evaluate and integrate emerging AI technologies, tools, and frameworks aligned with organizational goals.
  • Monitor and optimize deployed models for accuracy, performance, drift, reliability, and ethical considerations.
  • Partner with data engineering teams to ensure high-quality datasets and robust pipeline integrations.
  • Design, build, and deploy large language model (LLM) and agentic AI solutions, including multi-agent orchestration, tool use, autonomous workflows, and retrieval-augmented generation (RAG).
  • Optimize and deploy AI/ML models for edge environments, applying techniques such as quantization, pruning, and distillation to enable low-latency inference on resource-constrained and edge devices.

Work with us to solve real-world challenges and define ML strategy for law enforcement and homeland security clients.
Join us. The world can't wait.
You Have:
  • 8+ years of experience developing and deploying machine learning models in production environments
  • Experience in Python and ML frameworks
  • Experience with cloud platforms, such as AWS, Azure, or GCP, and tools for scalable ML systems, such as SageMaker, Azure ML, or Vertex AI
  • Experience building data pipelines
  • Experience with MLOps practices including CI/CD for ML, model versioning, monitoring, and deployment automation
  • Knowledge of ML algorithms, statistics, model optimization, and evaluation methodologies
  • Ability to design distributed systems and work with microservice-based architectures
  • Ability to communicate complex technical concepts clearly to non-technical stakeholders
  • Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
  • Bachelor's degree in a Computer Science, Data Science, or Engineering field

Nice If You Have:
  • Experience with LLMs, generative AI, RAG systems, and prompt engineering
  • Experience building agentic AI systems, including multi-agent frameworks, autonomous agents, tool and function calling, orchestration libraries such as LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI
  • Experience with edge AI optimization and deployment, including model quantization, pruning, and distillation, and deployment to edge and embedded hardware using frameworks such as TensorRT, ONNX Runtime, OpenVINO, or TensorFlow Lite
  • Experience with open-source containerization and container orchestration technologies, including Docker and Kubernetes
  • Experience with MLOps for production and machine learning workloads
  • Possession of strong problem-solving skills
  • Master's degree preferred; Doctorate degree a plus

Vetting:
Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $128,700.00 to $292,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date.
Identity Statement
As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.
Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.
  • Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
  • Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
  • Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
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About Booz Allen Hamilton

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Booz Allen Hamilton is a leading provider of management and technology consulting services to the US government in defense, intelligence, and civil markets. Headquartered in McLean, Virginia, the firm also serves major corporations, institutions, and not-for-profit organizations. Founded in 1914 by Edwin G. Booz, the company has a long-standing tradition of helping clients achieve success by delivering a wide range of consulting services that include strategic planning, human capital and learning, communication, systems development, and others. The company's mission is to empower people to change the world, and it has a reputation for maintaining the highest standards of integrity and-excellence.

Industry

It services

Company size

10,000+ Employees

Headquarters location

McLean, VA, US

Year founded

1914

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