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Remote Machine Learning Government Jobs in Leesburg, VA

Knexus

AI Software Engineer (Remote)

Vienna, VA · Remote

This role involves leveraging cutting-edge technologies, including GenAI and machine learning ... Government Clearance: You must be a U.S. citizen and eligible for a government security clearance ...

Maximus

Data Scientist (Remote)

VA · On-site +1

Government Secret security clearance or be eligible to obtain and maintain a Secret security ... NLP, and machine learning (both supervised and unsupervised) to improve relevance and ...

SAIC

AI SETA Systems Engineer

Chantilly, VA · On-site +1

$120K - $160K/yr

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a AI/Ml SETA Systems ... Provide technical and engineering support to the Government customer to manage machine learning ...

Booz Allen Hamilton, Inc.

AI/ML Engineer, Lead

Ashburn, VA · On-site +1

$104K - $138K/yr

Remote Work: Hybrid Job Number: R0246710 Location: Ashburn,VA,US Share job via: Share AI/ML ... As an AI/Machine Learning Engineer, you'll lead the design, development, and deployment of advanced ...

1872 Consulting

Principal Architect

Herndon, VA · On-site +1

Deep knowledge of machine learning processes and scalability solutions. Experience working with remote sensing data, ideally satellite imagery with an understanding of Geospatial software (GDAL ...

1872 Consulting

Principal Architect

Herndon, VA · On-site +1

Deep knowledge of machine learning processes and scalability solutions. Experience working with remote sensing data, ideally satellite imagery with an understanding of Geospatial software (GDAL ...

GRVTY

Data Scientist, Senior

Chantilly, VA · On-site +1

... technical government customer. What You'll be Owning * Develop and apply machine learning ... Experience with geospatial data, imagery products, or remote sensing datasets - familiarity with ...

GRVTY

Data Scientist, Senior

Chantilly, VA · On-site +1

... technical government customer. What You'll be Owning * Develop and apply machine learning ... Experience with geospatial data, imagery products, or remote sensing datasets -- familiarity with ...

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Showing results 21-40

All JobsMachine Learning Government JobsRemote Machine Learning Government JobsRemote Machine Learning Government Jobs in Leesburg, VA

Remote Machine Learning Government information

See Leesburg, VA salary details

$25.8K

$43.1K

$89K

How much do remote machine learning government jobs pay per year?

As of Sep 4, 2026, the average yearly pay for remote machine learning government in Leesburg, VA is $43,072.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,900.00 and $46,500.00 per year, depending on experience, location, and employer.

What job categories do people searching Remote Machine Learning Government jobs in Leesburg, VA look for?

The top searched job categories for Remote Machine Learning Government jobs in Leesburg, VA are:

What cities near Leesburg, VA are hiring for Remote Machine Learning Government jobs?

Cities near Leesburg, VA with the most Remote Machine Learning Government job openings:

Remote Machine Learning Government jobs near you
Infographic showing various Remote Machine Learning Government job openings in Leesburg, VA as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 30% Part Time, and 1% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $43,072 per year, or $20.7 per hour.

Senior Machine Learning Engineer, Radar & Remote Sensing

NT Concepts

Chantilly, VA • On-site, Remote

$107K - $146K/yr

Full-time

Posted 14 days ago

Job description

Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. We're looking for the best and the brightest to join us in supporting this mission. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, join our growing team and discover What's Next for you. We tackle hard problems to meet our clients' needs.
We are looking for an applied engineer to own our radar and ML technical stack. This is a blended role at the intersection of radar/SAR simulation, machine learning, scientific software, and compute infrastructure.
The ideal candidate is not a pure data scientist or a pure signal processing engineer. They are a technical owner who can move across the stack: from radar simulations and data preprocessing to ML model development, local GPU/compute setup, and hand-offs of radar products to software and hardware teams.
Clearance: Active TS/SCI clearance. US Citizenship is required.
Location: Chantilly, VA (Monday-Thursday Onsite & Friday Remote)
Responsibilities:
  • Act as a technical liaison, fostering effective communication and collaboration between radar engineering, machine learning, software engineering, and operation teams.
  • Develop and maintain robust radar and SAR simulation pipelines, including synthetic data generation, scene/return modeling, and validation workflows.
  • Design, build and refine end-to-end ML models and pipelines for radar-related tasks, including preprocessing, training, evaluation, and deployment-ready packaging.
  • Utilize and analyze defense-focused datasets, including radar, 3D models, Electro-Optical/Infrared (EO/IR), and sensing-adjacent data.
  • Create radar products and technical deliverables for internal software teams and hardware partners, including APIs, data schemas, containers, documentation, and integration guidance.
  • Design, configure, and optimize local compute environments, including GPU/eGPU setups, remote compute, storage, networking, containerization, and benchmarking.
  • Support ML inference/training on constrained or embedded compute, with awareness of systems such as RFSoCs, FPGAs, and related hardware constraints.
  • Collaborate with RF/hardware partners to support internal RF code processing, radar outputs, and productization of deployable radar hardware
  • Help deploy and maintain web applications and internal tools on classified or restricted networks.
  • Contribute to technical writing, SBIR proposals, and system documentation.

Required Qualifications:
  • Deep experience in Synthetic Aperture Radar, non-imaging radar, remote sensing, or signal processing
  • Solid understanding of radar/SAR fundamentals, including:
    • I/Q and complex-valued data
    • Simulation techniques
    • Image formation algorithms and radar-to-image pipelines
    • Coherent vs. incoherent processing
  • Proven track record of experience with radar or remote sensing simulations
  • Strong proficiency with scientific Python libraries:
    • NumPy, PyTorch, SciPy, Matplotlib, Jupyter, and related scientific stacks
  • Demonstrated ability to build end- to-end ML pipelines encompassing:
    • Data preprocessing
    • Training
    • Evaluation
    • Versioning
    • Packaging
    • Hand-off to other engineers
  • Hands-on experience with GPU compute, such as:
    • PyTorch
    • CUDA
    • NVIDIA tooling
    • Remote GPU Servers
    • Local GPU compute
  • Ability to explain radar/ML concepts to non-radar engineers and produce clear technical deliverables
  • Adherence to robust software engineering principles and best practices (e.g. clean code, testing, version control).
  • Exceptional communication skills, with the ability to clearly articulate complex radar and ML concepts to both technical and non-technical audiences, and to produce high-quality technical documentation and deliverables.

Preferred Skills/Experience:
  • Experience with Xpatch simulations specifically
  • Experience with CAD and or artistic 3D modeling skills
  • Experience with EO/IR or multi-sensor fusion
  • Experience with adversarial imaging AI
  • Understanding of RFSoCs, FPGAs, HLS, quantization, or edge deployment constraints
  • Experience designing or optimizing local compute servers / GPU clusters / eGPU configurations
  • Experience working with RF hardware partners or hardware-in-the-loop systems
  • Experience with LLMs, LoRA fine-tuning, or local model deployment for niche tasks
  • Experience with container computing and orchestration

Physical Requirements:
  • Prolonged periods sitting at a desk and working on a computer
  • Must be able to lift up to 10-15 pounds at time

#JT
The pay range listed for this position reflects the wage or salary range NT Concepts expects to pay for this role at the time of posting. The compensation offered to a successful candidate within this range will be based on legitimate, job-related factors, including (but not limited to) the candidate's work location, education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements.
Virginia Pay Range
$131,376-$243,984 USD
About NT Concepts
Founded in 1998 and headquartered in the Washington DC Metro area, NT Concepts is a private, mid-tier company with clients spanning the Intelligence and Defense communities. We deliver end-to-end data and technology solutions that advance the modernization, transformation, and automation of the national security mission-solutions with real impact developed in a strong engineering culture that encourages technical growth, leadership, and creative "big idea" problem-solving.
Employees are the core of NT Concepts. We understand that world-changing concepts happen in collaborative environments. We are a company where talented teams work together using innovation and expertise to solve our clients' most critical challenges. Here, you'll gain competitive benefits, opportunities to bolster your skills and develop new abilities, and a company culture dedicated to support and service. In addition to our benefits program, we encourage our employees to take part in #NTC_GivesBack, which paves the way for positive social change.
If joining a stable company with strong professional growth opportunities resonates with you, and you seek vital, mission-driven projects (for some pretty cool clients) that use your specific talents, we'd love to have you move forward with us.

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