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Artificial Intelligence Machine Learning Engineer Jobs in Leesburg, VA

SAIC

AI/Machine Learning Engineer Principal

Chantilly, VA · On-site

$120K - $160K/yr

ORA_ON_SITE Description SAIC seeks an Artificial Intelligence/Machine Learning Systems Engineer to join our team of professionals providing technical and program services to the U.S. Government (USG)

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All JobsArtificial Intelligence Machine Learning Engineer JobsArtificial Intelligence Machine Learning Engineer Jobs in Leesburg, VA

Artificial Intelligence Machine Learning Engineer information

See Leesburg, VA salary details

$31.9K

$130.2K

$195.7K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for artificial intelligence machine learning engineer in Leesburg, VA is $130,247.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,700.00 and $156,800.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

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

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

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

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

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

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What cities near Leesburg, VA are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Leesburg, VA with the most Artificial Intelligence Machine Learning Engineer job openings:

Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Leesburg, VA as of August 2026, with employment types broken down into 78% Full Time, 6% Part Time, and 16% Contract. Highlights an 81% In-person, 3% Hybrid, and 16% Remote job distribution, with an average salary of $130,247 per year, or $62.6 per hour.

Artificial Intelligence Machine Learning Engineer

ManTech International

Ashburn, VA • On-site

Full-time

Medical, Life, Retirement, PTO

Posted 23 days ago

ManTech rating

8.8

Company rating: 8.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

48th of 247 rated software companies

Job description

General information
Requisition #
R69977
Locations
USA-VA-Ashburn
Posting Date
08/12/2026
Security Clearance Required
Public Trust/Suitability
Remote Type
Hybrid
Time Type
Full time
Description & Requirements
Unlock the secrets of intelligence with MANTECH! Join a dynamic team at the forefront of national security, providing advanced solutions to government intelligence agencies. Since 1968, we've been solving the toughest challenges with groundbreaking tech. Explore thrilling projects in Digital Transformation, Cybersecurity, IT, Data Analytics and Software Development. Elevate your career and make a difference. Your adventure begins now-unleash your potential with MANTECH!
MANTECH seeks a motivated, career and customer-oriented Senior AI ML Engineer. This is currently a hybrid position with two to three days onsite in Ashburn, VA.
In this role, you will collaborate within a cross-functional team to develop new Artificial Intelligence/Machine Learning (AI/ML) based solutions into operational pipelines to deliver mission impact for U.S. Customs and Border Protection (CBP). The ideal candidate will have deep expertise and experience with predictive modeling lifecycles, hands-on experience with machine learning tools and frameworks, and a pragmatic, customer-centric approach to applying ML models to solve complex problems.
Each day CBP oversees the massive flow of people, capital, and products that enter and depart the United States via air, land, sea, and cyberspace. The volume and complexity of both physical and virtual border crossings require the application of solutions to aid officers in detecting threats while promoting efficient trade and travel.
Responsibilities include but are not limited to:
  • Lead the integration and deployment of trained AI/ML models into production environments (e.g., cloud, edge devices) using MLOps best practices.
  • Develop and optimize model training & inference pipelines for real-time execution and efficiently handle large-scale data processing.
  • Work with data science teams to structure automated ML model health monitoring and refresh capabilities.
  • Implement continuous integration, delivery and training (CI/CD/CT) workflows with commercial and open-source modeling platforms/services.
  • Coordinate with Data Science and Engineering teams to build scalable feature stores for optimal model training & execution workflows.
  • Research, evaluate and recommend new tools, applications, software packages for MLOps engineering that can be adopted and approved for use in the CBP environment.
  • Collaborate with cross-functional teams (e.g., Software Engineering, Data Science) to integrate and test multiple candidate AI/ML models and applications for operational assessment.

Required Qualifications:
  • HS Diploma/GED and 15-20 years of experience, AS/AA and 13-18 years, BS/BA and 7+ years or MS/MA/MBA and 5+ years or PhD/Doctorate and 3+ years.
  • Hands-on experience with LLMs such as Gemini, Llama, Mistral, or other open-source and commercial models. Experience with LLM application frameworks such as LangChain, LlamaIndex, or equivalent custom frameworks. Ability to optimize LLM systems for latency, throughput, scalability, reliability, GPU utilization, and inference cost. Experience deploying machine learning or LLM services in AWS, Azure, or Google Cloud. Demonstrated experience designing and deploying LLM solutions, including the following:
    • Retrieval-augmented generation (RAG)
    • Agentic workflows and tool calling
    • Prompt engineering and structured outputs
    • Model fine-tuning, e.g. LoRA
    • Embedding-based search and semantic retrieval
  • Strong understanding of transformer architectures, tokenization, embeddings, context windows, inference parameters, and common LLM failure modes. Experience evaluating LLM applications for accuracy, relevance, hallucination, safety, latency, and cost.
  • Experience with vector databases or search technologies such as OpenSearch, Elasticsearch, Milvus, Qdrant, Pinecone, Weaviate, or pgvector.
  • Experience designing and integrating RESTful APIs and microservices using frameworks such as FastAPI.
  • Working knowledge of SQL and experience with relational, document, or NoSQL databases.
  • Familiarity with Docker, Kubernetes, CI/CD pipelines, monitoring, logging, and production incident troubleshooting.

Preferred Qualifications
  • Master's degree or Ph.D. in Computer Science, Machine Learning, Natural Language Processing, or a related discipline.
  • Experience training, fine-tuning, quantizing, or serving open-source LLMs using tools such as PyTorch, Ollama, or TensorRT-LLM.
  • Understanding of AI security risks, including prompt injection, data leakage, unsafe tool execution, model abuse, and adversarial inputs. Experience building multi-agent systems, multimodal applications, long-context workflows, or human-in-the-loop AI systems.
  • Knowledge of advanced retrieval techniques, including hybrid search, reranking, query expansion, metadata filtering, and retrieval evaluation.
  • Experience in LLM projects from initial requirements and proof of concept through production deployment and ongoing optimization.
  • Strong knowledge of software engineering practices, including version control, code review, automated testing, system design, and technical documentation.

Clearance Requirements:
  • Must be a U.S. Citizen and be able to obtain and maintain a CBP suitability prior to start this position.
  • The ability to obtain and maintain a Top-Secret clearance.

Physical Requirements:
  • The person in this position needs to occasionally move about inside the office to access file cabinets, office machinery, or to communicate with co-workers, management, and customers, which may involve delivering presentations,

The projected compensation range for this position is $98,000.00-$163,100.00. There are differentiating factors that can impact a final salary/hourly rate, including, but not limited to, Contract Wage Determination, relevant work experience, skills and competencies that align to the specified role, geographic location (For Remote Opportunities), education and certifications as well as Federal Government Contract Labor categories. In addition, MANTECH invests in its employees beyond just compensation. MANTECH's benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, short-term and long-term Disability, Retirement and Savings, Learning and Development opportunities, wellness programs as well as other optional benefit elections.
MANTECH considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation.
If you need a reasonable accommodation to apply for a position with MANTECH, please email us at careers@mantech.com and provide your name and contact information.

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