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