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Machine Learning Engineer Jobs in Front Royal, VA

Parsons

Senior Software Engineer

Warrenton, VA · On-site

$150 - $200/hr

... helm, Machine Learning, Data Analytics, Android development, NoSQL and SQL databases, Xmidas are ... Join our team of experts as we engineer national security! #J-18808-Ljbffr

Bridge Core (BCore)

Systems Engineer

Warrenton, VA

$200K - $225K/yr

Overview Systems Engineer Warrenton / Tysons, VA TS/SCI with Poly At Bcore, our strength comes from ... Knowledge of machine learning platforms (e.g., TensorFlow, PyTorch, SageMaker) * Familiarity with ...

Bridge Core (BCore)

Systems Engineer

Warrenton, VA · On-site

$200K - $225K/yr

Overview Systems Engineer Warrenton / Tysons, VA TS/SCI with Poly At Bcore, our strength comes from ... Knowledge of machine learning platforms (e.g., TensorFlow, PyTorch, SageMaker) * Familiarity with ...

Bridge Core (BCore)

Systems Engineer

Warrenton, VA

$200K - $225K/yr

Systems Engineer Warrenton / Tysons, VA TS/SCI with Poly At Bcore, our strength comes from how we ... Knowledge of machine learning platforms (e.g., TensorFlow, PyTorch, SageMaker) * Familiarity with ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Front Royal, VA

Machine Learning Engineer information

See Front Royal, VA salary details

$29K

$118.5K

$178.1K

How much do machine learning engineer jobs pay per year?

As of Aug 27, 2026, the average yearly pay for machine learning engineer in Front Royal, VA is $118,508.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,400.00 and $142,600.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs

What cities near Front Royal, VA are hiring for Machine Learning Engineer jobs?

Cities near Front Royal, VA with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Front Royal, VA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $118,508 per year, or $57 per hour.

Sr. Solutions Engineer - Public Sector (DoW - 4th Estate)

Databricks

Washington, VA • On-site

$58.25 - $75/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
Databricks is the data and AI company that provides a unified analytics platform. The Sr. Solutions Engineer will lead the growth of the platform by partnering with customers, providing technical leadership, and consulting on big data architecture while building strong relationships.
Responsibilities:
• Partner with the sales team to help customers understand how Databricks can help solve their business problems
• Provide technical leadership for customers to evaluate and adopt Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present references architectures, how-tos, and demo applications for customers
• Become an expert in, and promote Databricks inspired open-source projects (Apache Spark™, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars
• Travel to customers in your region
Qualifications:
Required:
• 5+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in, and debugging, at least one of: Python, Scala, Java, SQL, or R
• Experience supporting Public Sector clients
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in at least one of the following: Data Engineering technologies (Ex: Spark, Hadoop, Kafka), Data Warehousing (Ex: SQL, OLTP/OLAP/DSS), Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, HPO)
• Secret security clearance or willingness to obtain one
Preferred:
• Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
Company:
Databricks is a data and AI platform that unifies data engineering, analytics, and machine learning on a lakehouse architecture. Founded in 2013, the company is headquartered in San Francisco, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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