Senior Machine Learning Engineer, Radar & Remote Sensing

Jobtailor; Chantilly (VA); On-site; USD 180,000 - 240,000; Full time

Job summary

Jobtailor seeks a senior radar/ML engineer to own the radar/SAR simulation stack and build end-to-end ML pipelines for radar tasks. You will liaise across radar engineering, ML, software engineering, and operations, delivering deployable models, synthetic data pipelines, and production-grade APIs.

You will work with constrained compute, RFSoCs, FPGAs, and GPU servers while contributing to SBIR proposals and system docs. Strong communication and writing are essential.

Qualifications

• Active TS/SCI clearance required.
• US Citizenship required.
• Deep experience in Synthetic Aperture Radar, non-imaging radar, remote sensing, or signal processing.
• Strong understanding of radar/SAR fundamentals, including I/Q and complex-valued data, simulation techniques, image formation algorithms and radar-to-image pipelines.
• Proven experience with radar or remote sensing simulations.
• Proficiency with scientific Python libraries (NumPy, PyTorch, SciPy, Matplotlib, Jupyter).
• Ability to build end-to-end ML pipelines (preprocessing, training, evaluation, packaging).
• Hands-on experience with GPU compute, CUDA, NVIDIA tooling, remote GPUs, and local GPU compute.
• Ability to explain radar/ML concepts to non-radar engineers and produce clear technical deliverables.
• Adherence to software engineering best practices (clean code, testing, version control).
• Exceptional communication and technical writing skills.
• Willingness to sit long hours at a desk and lift up to 10–15 pounds.

Responsibilities

• Own the radar and ML technical stack across radar/SAR simulation, ML, and compute infrastructure.
• Act as a technical liaison between radar engineering, ML, software engineering, and operations teams.
• Develop and maintain 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 tasks.
• Perform preprocessing, training, evaluation, and deployment-ready packaging.
• Utilize and analyze radar, 3D model, EO/IR, and sensing defense datasets.
• Create radar products and technical deliverables including APIs, data schemas, containers, documentation, and integration guidance.
• Design, configure, and optimize local compute environments, GPU/eGPU, remote compute, storage, networking, and benchmarking.
• Support ML inference/training on constrained/embedded compute (RFSoCs, FPGAs).
• Collaborate with RF/hardware partners on RF code processing, radar outputs, and deployable radar hardware productization.
• Help deploy and maintain web apps and internal tools on classified networks.
• Contribute to technical writing, SBIR proposals, and system documentation.

Skills

Radar Simulation

Machine Learning

NumPy

PyTorch

SciPy

CUDA

NVIDIA Tooling

Remote GPU Servers

Containerization

APIs

Version Control

Data Preprocessing

Image Formation

Scene/Return Modeling

Tools

Git

Python

Job description

• Own the radar and ML technical stack across radar/SAR simulation, machine learning, scientific software, and compute infrastructure
• Act as a technical liaison between radar engineering, machine learning, software engineering, and operations teams
• Develop and maintain 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
• Perform preprocessing, training, evaluation, and deployment-ready packaging
• Utilize and analyze radar, 3D model, EO/IR, and sensing‑adjacent defense datasets
• Create radar products and technical deliverables, including APIs, data schemas, containers, documentation, and integration guidance
• Design, configure, and optimize local compute environments, GPU/eGPU setups, remote compute, storage, networking, containerization, and benchmarking
• Support ML inference/training on constrained or embedded compute, including RFSoCs and FPGAs
• Collaborate with RF/hardware partners on RF code processing, radar outputs, and deployable radar hardware productization
• Help deploy and maintain web applications and internal tools on classified or restricted networks
• Contribute to technical writing, SBIR proposals, and system documentation

Requirements

• Active TS/SCI clearance
• US Citizenship is required
• 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, and coherent vs. incoherent processing
• Proven experience with radar or remote sensing simulations
• Strong proficiency with scientific Python libraries, including NumPy, PyTorch, SciPy, Matplotlib, Jupyter, and related scientific stacks
• Ability to build end-to-end ML pipelines encompassing data preprocessing, training, evaluation, versioning, packaging, and hand‑off to other engineers
• Hands‑on experience with GPU compute, including PyTorch, CUDA, NVIDIA tooling, remote GPU servers, and local GPU compute
• Ability to explain radar/ML concepts to non‑radar engineers and produce clear technical deliverables
• Adherence to software engineering principles and best practices, including clean code, testing, and version control
• Exceptional communication skills and ability to produce high‑quality technical documentation and deliverables
• Prolonged periods sitting at a desk and working on a computer
• Must be able to lift up to 10–15 pounds at a time

Core Competencies

Demonstrates expertise in Synthetic Aperture Radar and machine learning, with a strong ability to develop and maintain radar simulation pipelines and end-to-end ML models. Proficient in scientific Python libraries and GPU compute, with a focus on producing clear technical documentation and deliverables.

Highest‑signal resume keywords

• Synthetic Aperture Radar Expertise
• End‑to‑End ML Pipeline Development
• Scientific Python Proficiency
• GPU Compute Experience

  ATS Optimization Keywords

  Hard Skills

  • Radar Simulation
  • Machine Learning Models
  • Data Preprocessing
  • Image Formation Algorithms
  • Version Control
  • Testing Best Practices
  • Synthetic Data Generation
  • Scene/Return Modeling
  • Coherent Processing
  • Non‑Imaging Radar

  Soft Skills

  • Exceptional Communication Skills
  • Technical Writing

  Certifications & Qualifications

  • Active TS/SCI Clearance
  • US Citizenship

  Industry Keywords

  • Remote Sensing
  • Signal Processing
  • Radar Fundamentals
  • RF Code Processing
  • Embedded Compute
  • Technical Deliverables
  • SBIR Proposals
  • Compute Infrastructure
  • Data Schemas
  • Integration Guidance

  Tools & Technologies

  • NumPy
  • PyTorch
  • SciPy
  • Matplotlib
  • Jupyter
  • CUDA
  • NVIDIA Tooling
  • Remote GPU Servers
  • Containerization
  • APIs