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Junior Machine Learning Engineer Jobs in Quantico, VA

Mid-Level Software Engineer

Fairfax, VA · On-site

$90K - $180K/yr

Position Overview As a Mid-Level Machine Learning/AI Software Engineer, you will be responsible for developing, implementing, and applying machine learning/AI algorithms and solutions to address ...

New

Data Scientist, Mid

Springfield, VA · On-site

$77.60 - $176/hr

  • Medical

  • Life

  • Retirement

  • PTO

Provide mentorship to junior analysts and support continuous improvement of analytic best practices ... Professional certifications such as Google Professional Machine Learning Engineer, Azure Data ...

Quantum Engineer SME

Springfield, VA

$86K - $114K/yr

Apply principles and methods from quantum machine learning and related quantum computing fields to address highly complex, narrowly scoped technical challenges in engineering and other scientific ...

Quantum Engineer SME

Springfield, VA · On-site

$86K - $115K/yr

Apply principles and methods from quantum machine learning and related quantum computing fields to address highly complex, narrowly scoped technical challenges in engineering and other scientific ...

Quantum Engineer SME

Springfield, VA · On-site

$86K - $115K/yr

Apply principles and methods from quantum machine learning and related quantum computing fields to address highly complex, narrowly scoped technical challenges in engineering and other scientific ...

Data Scientist, Mid

Springfield, VA · On-site

  • Medical

  • Life

  • Retirement

  • PTO

Provide mentorship to junior analysts and support continuous improvement of analytic best practices ... Professional Certifications such as Google Professional Machine Learning Engineer, Azure Data ...

Data Scientist, Mid

Springfield, VA · On-site

  • Medical

  • Life

  • Retirement

  • PTO

Provide mentorship to junior analysts and support continuous improvement of analytic best practices ... Professional Certifications such as Google Professional Machine Learning Engineer, Azure Data ...

Data Scientist, Mid

Springfield, VA · On-site

  • Medical

  • Life

  • Retirement

  • PTO

Provide mentorship to junior analysts and support continuous improvement of analytic best practices ... Professional Certifications such as Google Professional Machine Learning Engineer, Azure Data ...

Data Scientist, Mid

Springfield, VA · On-site

  • Medical

  • Life

  • Retirement

  • PTO

Provide mentorship to junior analysts and support continuous improvement of analytic best practices ... Professional Certifications such as Google Professional Machine Learning Engineer, Azure Data ...

Showing results 41-60

Junior Machine Learning Engineer information

See Quantico, VA salary details

$35.5K

$76K

$116K

How much do junior machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for junior machine learning engineer in Quantico, VA is $76,050.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,400.00 and $84,700.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

What are the most commonly searched types of Machine Learning Engineer jobs in Quantico, VA?

The most popular types of Machine Learning Engineer jobs in Quantico, VA are:

What are popular job titles related to Junior Machine Learning Engineer jobs in Quantico, VA?

For Junior Machine Learning Engineer jobs in Quantico, VA, the most frequently searched job titles are:

What cities near Quantico, VA are hiring for Junior Machine Learning Engineer jobs?

Cities near Quantico, VA with the most Junior Machine Learning Engineer job openings:

Infographic showing various Junior Machine Learning Engineer job openings in Quantico, VA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $76,050 per year, or $36.6 per hour.

Software Engineer (Full Stack) - SME with Security Clearance

GRVTY

Springfield, VA • On-site

Other

Re-posted 24 days ago


Job description

What Impact You'll Have: Join a mission-focused team where your work directly supports critical national security objectives. We are seeking a Subject Matter Expert (SME) Full Stack Developer to lead the design, development, and delivery of scalable, mission-driven applications within an ML/Ops environment. This role combines deep technical expertise with advanced system-level thinking and close collaboration across engineering, data science, and customer stakeholder teams. The Full Stack Developer will perform rapid application design, ETL, data analysis, and interpretation while developing rules and methodologies for data collection and analysis. You will architect, develop, and maintain a Python-based data warehouse processing system that serves as the backend for a user-facing application, while also leading development of modern GUI applications using REST APIs and contemporary web frameworks. You will work closely with data scientists, computer vision engineers, ETL engineers, and intelligence analysts to integrate machine learning capabilities into production systems, enabling scalable model deployment, monitoring, and continuous improvement. This role emphasizes ownership, technical leadership, and delivery of production-ready solutions that operate reliably in dynamic, real-world environments. What You'll Be Owning: • Lead and participate in the architectural design of complex features early in the development lifecycle. • Translate customer requirements and roadmap priorities into technical solutions, tasks, timelines, and resource plans. • Develop, integrate, and maintain full stack applications supporting ML/Ops pipelines and data-driven systems. • Design and implement scalable APIs and services to support machine learning model deployment and inference. • Develop and maintain data pipelines, ETL processes, and data storage solutions for large-scale datasets. • Collaborate with data scientists and ML engineers to operationalize models within production environments. • Optimize application and system performance for scalability, reliability, and efficiency, including edge and distributed environments when applicable. • Conduct peer reviews and establish coding standards to improve overall code quality and maintainability. • Guide development testing, exploratory testing, automated testing, and validation strategies. • Own code in production environments, respond to incidents, and lead root cause analysis and continuous improvement efforts. • Ensure security, compliance, and governance are maintained throughout the development lifecycle. • Perform technical planning, system integration, verification and validation, and risk assessments across system components. • Mentor and develop junior and mid-level engineers, fostering technical growth and high-performing teams. • Drive adoption of modern ML/Ops practices, tools, and automation frameworks across the team. What You Must Have: • Active TS/SCI clearance with the ability to obtain a CI poly • Bachelor's degree in Computer Science, Engineering, or a related technical field. • 14+ years of professional experience in full stack software development. • Expert-level proficiency in Python and object-oriented design patterns. • Extensive experience developing backend systems, APIs, and data processing pipelines. • Strong experience with modern web development frameworks, including React.js, Node.js, and/or Electron. • Deep understanding of data modeling techniques and experience working with large-scale and time series datasets. • Experience with relational and non-relational databases such as PostgreSQL, MongoDB, and BigQuery. • Experience building and maintaining RESTful APIs and microservices architectures. • Experience supporting machine learning workflows, including model integration, deployment, and monitoring. • Familiarity with ML/Ops tools and utilities such as MLflow, DVC, and/or Optuna. • Strong experience with Python libraries such as NumPy and Pandas. • Experience with Python web frameworks such as Flask, FastAPI, Pydantic, Gunicorn, and Uvicorn. • Experience with containerization and DevOps practices, including Docker and CI/CD pipelines. • Experience with web servers such as Apache and Nginx. • Experience working within Agile development environments and using associated tools. What Would be Nice to Have: • Experience supporting government or defense-related programs. • Experience integrating computer vision or machine learning capabilities into operational systems. • Knowledge of real-time data processing, streaming architectures, or distributed systems. • Experience with cloud-based ML/Ops environments and infrastructure (AWS, Azure, or Google Cloud Platform). • Experience with parallelization and multiprocessing frameworks such as Dask. • Knowledge of geospatial data processing tools and libraries including GeoPandas, Shapely, Rasterio, QGIS, and ArcPy. • Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. • Experience with remote procedure call technologies such as gRPC and JSON-RPC. #LI-CM1