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Applied Machine Learning Jobs in Virginia (NOW HIRING)

Radiance Technologies

Data Scientist

Dahlgren, VA

Strong knowledge of data imputation techniques and applied machine learning * Familiarity with defense-related analytics or operational modeling preferred At Radiance Technologies , your work has ...

Radiance Technologies

Data Scientist

Dahlgren, VA · On-site

Strong knowledge of data imputation techniques and applied machine learning * Familiarity with defense-related analytics or operational modeling preferred At Radiance Technologies , your work has ...

Cmu

AI Security Software Engineer

Arlington, VA · On-site +1

Familiarity with applied machine learning domains (e.g., natural language processing, computer vision, autonomy, audio analysis) * Experience and knowledge in cybersecurity best practices

Qualtrics

Senior Applied Scientist

Reston, VA · On-site

$95K - $130K/yr

Applied scientists partner with application teams to deliver algorithms and models that drive ... Leverage your deep knowledge of AI principles, including machine learning, natural language ...

Qualtrics

Senior Applied Scientist

Reston, VA

$95K - $130K/yr

Applied scientists partner with application teams to deliver algorithms and models that drive ... Leverage your deep knowledge of AI principles, including machine learning, natural language ...

Capital One

Applied Researcher II

Mclean, VA

Applied Researcher II Overview: At Capital One, we are creating trustworthy and reliable AI systems ... For years, Capital One has been leading the industry in using machine learning to create real-time ...

Capital One

Applied Researcher II

Mclean, VA · On-site

Applied Researcher II Overview: At Capital One, we are creating trustworthy and reliable AI systems ... For years, Capital One has been leading the industry in using machine learning to create real-time ...

Capital One

Applied Researcher II

Mclean, VA · On-site

Applied Researcher II Overview: At Capital One, we are creating trustworthy and reliable AI systems ... For years, Capital One has been leading the industry in using machine learning to create real-time ...

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Applied Machine Learning information

See Virginia salary details

$25.3K

$42.2K

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How much do applied machine learning jobs pay per year?

As of Jul 20, 2026, the average yearly pay for applied machine learning in Virginia is $42,218.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

What are the typical collaboration dynamics between Applied Machine Learning engineers and other teams within a company?

Applied Machine Learning engineers often work closely with cross-functional teams including data scientists, software engineers, product managers, and business analysts. They are typically responsible for translating business problems into machine learning solutions and ensuring models are effectively integrated into production systems. This role requires frequent communication to align on project goals, share progress, and address technical challenges, making teamwork and stakeholder management crucial for successful deployments and continuous improvement.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms. Compensation at this level reflects significant expertise, responsibility, and impact on business or product development.

What is applied machine learning?

Applied machine learning involves using machine learning techniques and algorithms to solve real-world problems in various industries, such as healthcare, finance, and technology. Practitioners focus on selecting appropriate models, preparing data, training algorithms, and deploying solutions that deliver tangible value. Unlike theoretical machine learning, applied machine learning emphasizes practical implementation, evaluation, and optimization to meet business or research objectives.

Is applied AI a good career?

Applied machine learning is a growing field with strong demand for professionals skilled in algorithms, programming, and data analysis. It offers opportunities in various industries such as technology, healthcare, and finance, often requiring knowledge of tools like Python, TensorFlow, and cloud platforms. The career can be rewarding with continuous learning and development of specialized skills.

What are the key skills and qualifications needed to thrive as an Applied Machine Learning professional, and why are they important?

To excel in Applied Machine Learning, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a relevant degree or certification. Familiarity with programming languages like Python or R, frameworks such as TensorFlow or PyTorch, and version control systems is typically required. Strong problem-solving abilities, communication skills, and a collaborative mindset help you interpret results and convey insights to diverse stakeholders. These competencies are crucial for building effective models, driving data-driven decisions, and ensuring the successful integration of machine learning solutions into real-world applications.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries or companies can earn $500,000 or more annually. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of successful projects in applied machine learning environments.

Will MLE be replaced by AI?

Applied Machine Learning (MLE) professionals design, develop, and implement machine learning models, which are essential for AI systems. While AI automation tools can assist or streamline certain tasks, MLE roles focus on model development, data preprocessing, and system integration that require specialized expertise, making complete replacement unlikely in the near term.
What are popular job titles related to Applied Machine Learning jobs in Virginia? For Applied Machine Learning jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Applied Machine Learning jobs in Virginia look for? The top searched job categories for Applied Machine Learning jobs in Virginia are:
Applied Machine Learning jobs near you
Infographic showing various Applied Machine Learning job openings in Virginia as of July 2026, with employment types broken down into 75% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $42,218 per year, or $20.3 per hour.
Machine Learning Engineer (Applied ML/MIssion Systems) - R133

Machine Learning Engineer (Applied ML/MIssion Systems) - R133

Expedition Technology

Herndon, VA • On-site

Full-time

Re-posted 12 days ago

Job description

Job Summary:
Expedition Technology is seeking a Machine Learning Engineer to join a fast-paced development program focused on operational capabilities. The role involves designing, prototyping, and iterating on machine learning models and data pipelines to address real-world mission problems, particularly in temporal and geospatial data analytics.
Responsibilities:
• Design, develop, and deploy machine learning models and pipelines for real-world mission applications
• Work with temporal and track-based datasets (e.g., entity tracking, time-series, geospatial data)
• Build data processing and feature engineering workflows to support model training and evaluation
• Operationalize models using containerized, cloud-native infrastructure (AWS, Docker, Kubernetes)
• Collaborate with engineers and analysts to translate mission needs into ML-driven solutions
• Develop and integrate APIs and services that expose model outputs to downstream systems
• Optimize models and pipelines for performance, scalability, and reliability
• Contribute to experimentation frameworks, model evaluation, and continuous improvement workflows
• Participate in Agile development, code reviews, and engineering best practices
Qualifications:
Required:
• U.S. Citizenship
• Active TS/SCI clearance
• 5+ years of experience in machine learning, data engineering, or backend software engineering
• Strong programming skills in Python
• Experience developing or supporting machine learning models in production environments
• Familiarity with: Machine learning frameworks (e.g., PyTorch, TensorFlow, or similar)
• Data processing and analysis (NumPy, Pandas, etc.)
• Understanding of core ML concepts (supervised/unsupervised learning, feature engineering, evaluation)
• Experience with cloud environments (AWS preferred)
• Familiarity with Docker, Kubernetes, or other containerized systems
• Experience working with Linux environments
• Knowledge of Git and modern software development practices (SDLC, CI/CD)
Preferred:
• Experience working with track, time-series, or geospatial data
• Familiarity with maritime domain data or analytics
• Understanding of probabilistic modeling, filtering, or tracking algorithms (e.g., Kalman filters, multi-object tracking)
• Experience building end-to-end ML pipelines (data ingestion → training → deployment → monitoring)
• Exposure to distributed data processing frameworks
• Experience deploying ML systems in classified or mission environments
Company:
Expedition Technology is an engineering firm that specializes in advanced research for a broad range of government customers. Founded in 2013, the company is headquartered in Herndon, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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