Senior Machine Learning Engineer, Radar & Remote Sensing

Next Tier Concepts; Chantilly (VA); Hybrid; USD 140,000 - 170,000; Full time

Job summary

Next Tier Concepts in Chantilly, VA seeks an applied machine learning engineer to own radar and ML technical stack. The role spans radar/SAR simulation, ML model development, and compute infrastructure, with on-site Mon–Thu and remote on Friday.

Active TS/SCI clearance and US citizenship required. You will build end-to-end ML pipelines, manage data preprocessing, training, evaluation, packaging, and hand-off to software and hardware teams, while collaborating across RF and defense-focused

Qualifications

• Deep experience in SAR, non-imaging radar, remote sensing, or signal processing.
• Strong understanding of radar/SAR fundamentals including I/Q data and image formation.
• Proven ability to build end-to-end ML pipelines for radar tasks.
• Hands-on GPU compute with PyTorch, CUDA, and NVIDIA tooling.
• Ability to explain radar/ML concepts to non-radar engineers and document Deliverables.

Responsibilities

• Act as a technical liaison across radar engineering, ML, software, and operations.
• Develop and maintain radar and SAR simulation pipelines with synthetic data.
• Design end-to-end ML models and packaging for deployment.
• Work with RF/hardware partners on radar code processing and productization.
• Configure local compute environments with GPU/remote compute and containers.
• Support ML inference/training on constrained hardware (RFSoCs, FPGAs).
• Create technical deliverables, APIs, data schemas, and documentation.
• Contribute to SBIR proposals and system documentation.

Skills

Synthetic Aperture Radar

radar fundamentals

scientific Python

ML pipelines

GPU compute

PyTorch

CUDA

remote sensing

data preprocessing

communication

Tools

NumPy

SciPy

Matplotlib

Jupyter

Job description

Chantilly, VA

Position Title: Senior Machine Learning Engineer, Radar & Remote Sensing

Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. Were 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- 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