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Senior Machine Learning Engineer Jobs in Broad Run, VA

Pantheon Data

Senior Machine Learning Engineer

Reston, VA · On-site

$140K - $200K/yr

Position Overview Pantheon Data is seeking a Senior Machine Learning Engineer to design, build, and operate production AI systems for federal clients - including hybrid retrieval-augmented generation ...

Pantheon Data LLC

Senior Machine Learning Engineer

Reston, VA · Hybrid

$108K - $149K/yr

Position Overview Pantheon Data is seeking a Senior Machine Learning Engineer to design, build, and operate production AI systems for federal clients - including hybrid retrieval-augmented generation ...

Pantheon Data

Senior Machine Learning Engineer

Reston, VA · Remote

$140K - $200K/yr

Position OverviewPantheon Data is seeking a Senior Machine Learning Engineer to design, build, and operate production AI systems for federal clients - including hybrid retrieval-augmented generation ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Cymertek Corporation

Machine Learning Engineer

Reston, VA · On-site

$110 - $170/hr

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

1872 Consulting

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer D.C. Area About the Position As a member of our Engineering team, you will work with a tight, highly skilled machine learning / data science team dedicated to the ...

1872 Consulting

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer D.C. Area About the Position As a member of our Engineering team, you will work with a tight, highly skilled machine learning / data science team dedicated to the ...

Unissant

Machine Learning Engineer

Ashburn, VA · On-site

$110 - $170/hr

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands‑on experience in machine learning, advanced analytics, and ...

UNISSANT

Machine Learning Engineer

Ashburn, VA · On-site

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands-on experience in machine learning, advanced analytics, and AI ...

AIToolboard

Machine Learning Engineer- Senior

Chantilly, VA · On-site

$140 - $190/hr

# Machine Learning Engineer- SeniorSOSiChantilly, USFull-time## About the RoleCompany DescriptionFounded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Broad Run, VA

Senior Machine Learning Engineer information

See Broad Run, VA salary details

$57.5K

$122.4K

$177.4K

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

As of Sep 5, 2026, the average yearly pay for senior machine learning engineer in Broad Run, VA is $122,381.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,100.00 and $138,800.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What cities near Broad Run, VA are hiring for Senior Machine Learning Engineer jobs?

Cities near Broad Run, VA with the most Senior Machine Learning Engineer job openings:

Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Broad Run, VA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,381 per year, or $58.8 per hour.

Senior Machine Learning Engineer

Pantheon Data

Reston, VA • On-site

$140K - $200K/yr

Full-time

Posted 9 days ago

Job description

Company Overview
Pantheon Data (a Kenific Holding company) is a private, small business based in the Washington, DC, area. Pantheon Data was founded in 2011, initially providing acquisition and supply chain management services to the US Coast Guard. Our service offerings have grown in the past ten years, including infrastructure resiliency, contact center operations, information technology, software engineering, program management, strategic communications, engineering, and cybersecurity. We have also grown our customer base to include commercial clients. The company has used this experience to expand our service offerings to other agencies within the Department of Homeland Security (DHS), the Department of Defense (DoD), and other Federal Civilian Agencies.
Position Overview
Pantheon Data is seeking a Senior Machine Learning Engineer to design, build, and operate production AI systems for federal clients - including hybrid retrieval-augmented generation (RAG) applications, Intelligent Document Processing (IDP) pipelines, and LLM-backed decision-support tools running in AWS GovCloud.
This is a hands-on, production-focused engineering role. You will work with GovCloud-hosted foundation models on Amazon Bedrock, build hybrid retrieval over relational and vector data stores, design rigorous evaluation harnesses, and ship secure, traceable, evidence-grounded systems in FedRAMP High / DoD IL4-IL5 environments. This is not a notebook-only, prompt-only, or research-only role: successful candidates can walk through real systems they have built - the data flow, retrieval and inference architecture, deployment approach, evaluation strategy, failure modes, and what they personally implemented.
What This Role Will Work On
  • Design and build hybrid RAG applications combining semantic (vector) search, lexical/full-text search, and structured SQL retrieval, with rank fusion, evidence grounding, and source-cited answer generation.
  • Integrate and operate GovCloud-hosted LLMs and embedding models via Amazon Bedrock (e.g., Anthropic Claude, Amazon Titan embeddings), including prompt/version management, guardrails, streaming inference, and cost/latency tuning.
  • Build Intelligent Document Processing capabilities: OCR post-processing, layout-aware parsing, table and form extraction, NLP/LLM structured extraction, chunking and embedding strategies, and human-in-the-loop review workflows.
  • Develop serverless, event-driven ingestion pipelines (AWS Step Functions, Lambda, S3, Aurora PostgreSQL with pgvector) that turn messy source documents into reliable, traceable, queryable information.
  • Design and run evaluation programs for retrieval quality, extraction accuracy, answer groundedness, hallucination risk, and end-to-end system performance - including golden datasets, automated eval harnesses in CI, and regression testing across model and prompt versions.
  • Engineer for security and compliance from the start: least-privilege IAM, private VPC endpoints and restricted-egress network boundaries, guardrails and prompt-injection defenses, output validation, audit logging, and CUI-aware data handling in support of ATO requirements.
  • Make practical engineering decisions about when to use deterministic logic, classical NLP, OCR, embeddings, LLMs, fine-tuned or distilled models, or human review - and defend those tradeoffs to technical and non-technical stakeholders.

Responsibilities
  • Design, implement, and maintain ML/AI software components for RAG, IDP, and generative AI systems serving federal customers.
  • Build and operate data pipelines for unstructured and semi-structured data: ingestion, extraction, cleaning, enrichment, validation, quality scoring, quarantine/review, and storage.
  • Develop and evaluate NLP, OCR, computer vision, embedding, retrieval, and LLM-based approaches for document understanding and question answering.
  • Contribute production-quality Python with clear structure, tests, logging, error handling, and documentation; participate in code review and team-based delivery.
  • Deploy and support AI services in cloud and containerized environments, including Bedrock model integration, batch processing, workflow orchestration, and observability (CloudWatch, tracing, structured logs).
  • Define evaluation methodology and metrics; build eval datasets and harnesses; analyze errors; and drive iterative improvement of retrieval and generation quality.
  • Implement responsible-AI and security controls: Bedrock Guardrails or equivalent, PII/sensitive-data redaction, content filtering, prompt-injection mitigation, and output traceability to source evidence.
  • Troubleshoot system behavior across model output, data quality, retrieval, schema design, infrastructure, latency, cost, and user workflow.
  • Mentor other engineers, help establish standards for evaluation, reproducibility, and responsible AI use, and raise the technical quality of the team.
  • Communicate clearly with technical and non-technical stakeholders, including project managers, customers, and executive leadership.

Required Skills and Experience
  • Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related technical field, or equivalent professional experience.
  • 8+ years of professional software engineering experience, including 5+ years hands-on in machine learning / AI engineering or a closely related role.
  • Demonstrated experience shipping AI/ML systems beyond notebooks and demos: production pipelines, services, APIs, inference endpoints, evaluation harnesses, or customer-facing tools you built and supported.
  • Hands-on experience building LLM-backed applications with managed foundation-model services - Amazon Bedrock strongly preferred (Claude, Titan, or similar models), ideally in AWS GovCloud or another regulated/isolated environment.
  • Deep experience with RAG architectures: embeddings, vector search (pgvector or comparable), hybrid retrieval (semantic + lexical + structured), chunking strategies, re-ranking or rank fusion, and citation/evidence grounding.
  • Experience designing and running LLM/RAG evaluations: retrieval and answer-quality metrics, groundedness and hallucination measurement, golden datasets, automated regression evals, and human-in-the-loop validation.
  • Strong Python engineering skills: readable, maintainable, tested code; debugging; packaging; and integration with other systems.
  • Experience with AWS services relevant to this stack: Lambda, Step Functions, S3, IAM, CloudWatch, and relational databases (PostgreSQL preferred).
  • Experience working with unstructured or semi-structured data: PDFs, scanned documents, forms, tables, technical manuals, drawings, or engineering documentation.
  • Working knowledge of AI security practices: guardrails, prompt-injection defenses, output validation, data redaction, and least-privilege access patterns.
  • Ability to design and reason about end-to-end data flow: source data, preprocessing, retrieval, model/inference step, persistence, API/service boundary, evaluation, and user-facing output.
  • Experience with Git-based workflows, code review, CI/CD, and team-based software delivery.
  • Clear written and verbal communication, including explaining tradeoffs, limitations, and failure modes.
  • Ability to work effectively remotely in cross-functional teams.
  • Ability to meet deadlines and produce quality work.
  • Proficient in Microsoft Suite software including Outlook, Word, Excel, SharePoint, and PowerPoint.

Preferred Skills and Experience
  • Direct experience operating LLM workloads in AWS GovCloud under FedRAMP High or DoD IL4/IL5, including private VPC endpoints, zero- or restricted-egress boundaries, and ATO-supporting documentation.
  • Experience with Bedrock features beyond basic inference: Guardrails, Knowledge Bases, Agents, Model Evaluation, provisioned throughput, and cross-model routing.
  • Intelligent Document Processing depth: OCR pipelines (e.g., Textract), layout-aware models, table/form extraction, and document quality scoring.
  • Familiarity with federal compliance frameworks and their engineering implications: NIST 800-53, CMMC, CUI handling, SBOM/supply-chain controls, and STIG-hardened environments.
  • Experience with infrastructure as code (Terraform), containerized deployment (Docker/ECS), and CI/CD pipelines (GitLab CI or GitHub Actions) in regulated environments.
  • Experience with observability and LLMOps tooling: structured logging, tracing, model/prompt version management, drift detection, and cost/latency dashboards.
  • Experience building internal validation tools, review interfaces, dashboards, or lightweight full-stack applications (e.g., Next.js/React front ends over Python services).
  • Familiarity with common ML frameworks and tooling: PyTorch, Hugging Face, scikit-learn, MLflow, or similar.
  • Advanced degree in a technical discipline.
  • Demonstrated mentorship of junior engineers or contribution to team technical direction.

Clearance Requirements
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements. Secret Clearance is required for continued employment.
Work Location: Reston, VA - Remote
  • Our company prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely.
  • If the position is remote or hybrid, you may periodically work from a Pantheon Data office location or client site.
  • If this position is assigned to a Pantheon Data office location or client site, you'll work with colleagues and clients in person, as needed for specific client requirements.

Interview Requirement: Candidates who are local to the area should be prepared to participate in an in-person interview as part of the selection process. Candidates outside the local area may be considered for a virtual interview.
Compensation
The salary range for this position is $140,000 - $200,000. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.
Benefits Overview
We are always looking for good people! Pantheon Data is committed to providing its employees with competitive salaries and benefits in order to increase employee satisfaction and productivity. In addition to our benefits, we also offer SmartBenefits through the Washington Metro Area Transportation Authority, where you specify an amount of your pre-tax wages be paid directly to your SmarTrip account. In some cases, tuition assistance may be available for continuing education expenses and certifications related to their position. Additional details may be found at
Pantheon Data Important Information
All qualified applicants will be considered for employment without regard to disability, status as a protected veteran, or any other status protected by applicable federal, state, local, or international law.
As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to our Talent Team at or by phone (571) 363-4020.
This company uses E-Verify to confirm each employee's work authorization. For more information, click here

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