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Applied Machine Learning Jobs in Virginia (NOW HIRING)

Capital One

Lead Machine Learning Engineer

Mclean, VA

$103K - $136K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... We are committed to continuing to build world-class applied science and engineering teams to ...

Capital One

Lead Machine Learning Engineer

Richmond, VA · On-site

$101K - $133K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... We are committed to continuing to build world-class applied science and engineering teams to ...

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

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 ...

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All JobsApplied Machine Learning JobsApplied Machine Learning Jobs in Virginia

Applied Machine Learning information

See Virginia salary details

$25.3K

$42.2K

$87.2K

How much do applied machine learning jobs pay per year?

As of Jun 29, 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.

Which 3 jobs will survive AI?

Applied Machine Learning professionals, data scientists, and AI system engineers are likely to continue thriving as AI advances, due to their expertise in developing, managing, and interpreting complex models. These roles require specialized skills in programming, statistical analysis, and domain knowledge, making them less susceptible to automation. Continuous learning and staying updated with new tools like TensorFlow or PyTorch are essential for long-term job security in this field.

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 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 high 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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying scalable AI systems can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires strong programming skills, knowledge of cloud platforms, and a track record of impactful projects.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. Such roles usually involve leadership responsibilities, strategic planning, and may require multiple years of industry experience and relevant certifications.
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

Machine Learning Engineer with Security Clearance

Eiden Systems Consulting

Sterling, VA • On-site

Other

Medical, Dental, Vision, Life, Retirement

Posted 18 days ago

Job description

Eiden Systems Consulting is seeking a Mid-Level Machine Learning Engineer to support a mission-focused R&D program developing advanced signal detection and classification capabilities for national security applications. This role focuses on designing, training, and deploying ML models capable of identifying complex signals within high-bandwidth sensors and I/Q data streams. The engineer will work closely with researchers and software engineers to transition prototype algorithms into low-latency, edge-deployed operational systems supporting real-world mission environments.

Responsibilities: • Design, develop, and optimize machine learning models for signal detection, classification, and anomaly detection within noisy and high-volume data streams • Develop and tune deep learning architectures including CNNs, LSTMs, and Transformer-based models for temporal and sequence-based analysis • Apply signal processing techniques such as Fourier and wavelet transforms to support feature extraction and model performance • Build scalable data pipelines for real-time I/Q stream processing, including buffering, windowing, normalization, and inference workflows • Evaluate model effectiveness using advanced performance metrics including ROC/AUC, precision-recall curves, confusion matrices, and other techniques for imbalanced datasets • Optimize machine learning models for low-latency execution on edge and embedded hardware platforms • Develop modular, maintainable, and testable code using Python, NumPy, PyTorch and/or TensorFlow • Support integration with network-attached sensors, hardware abstraction layers, and real-time data sources • Collaborate with software engineers, researchers, and mission stakeholders in an agile R&D environment • Participate in code reviews, technical discussions, and continuous improvement efforts using GitLab-based development workflows • Support containerized application development and deployment using Docker within Linux/Unix environments Required Qualifications: • Experience: 4-7 years of professional experience in machine learning or data science, with at least 2 years focused on sensor-based or temporal data. • Education: B.S. or M.S.

in computer science, data science, or applied mathematics. • Security clearance: Active Top Secret (TS) clearance required. SCI preferred.

• Hands-on experience developing and deploying machine learning models using PyTorch and/or TensorFlow • Strong understanding of machine learning fundamentals, statistics, linear algebra, and probability • Experience developing software in Linux/Unix environments • Proficiency in Python and scientific computing libraries such as NumPy • Experience with version control and collaborative development workflows • Experience working with I/Q data streams and real-time inference pipelines ESC offers a competitive compensation package that includes premium health, dental, and vision insurance, a 401(k) plan with company match, life insurance, short- and long-term disability coverage, and more. We also prioritize work-life balance, supporting our team in maintaining a healthy blend of professional and personal well-being. PAY TRANSPARENCY NONDISCRIMINATION PROVISION Eiden Systems Consulting (ESC) is an equal opportunity employer and is committed to creating an inclusive and respectful workplace.

ESC does not discriminate against any employee or applicant based on age, color, disability, gender, national origin, race, religion, sexual orientation, veteran status, or any other classification protected by federal, state, or local law. In accordance with 41 CFR 60-1.35(c), ESC will not discharge or otherwise discriminate against employees or applicants for discussing, disclosing, or inquiring about their own pay or the pay of another employee or applicant. However, employees who have access to compensation information as part of their essential job functions may not disclose the pay of others to individuals who do not have authorized access—unless such disclosure is made (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or legal action (including those conducted by ESC), or (c) as otherwise required by law.

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