Data Scientist and Machine Learning Engineer (US Citizen – Clearance Eligible)

Company Description Stealth-24 is an early-stage hard-tech and AI-enabled startup operating in stealth mode. Our mission is to deliver innovative solutions at the intersection of aerospace, defense, and advanced computing. We are building a dynamic, world-class team of engineers and entrepreneurs tackling vital national security challenges with modern, software-defined systems. Our customers represent some of the most respected organizations in government and industry, though details remain confidential. Your work will directly support U.S. national security missions and accelerate the deployment of next-generation aerospace and defense systems. Role Description This is a full-time, remote role for a Senior/Staff Data Scientist & Machine Learning Engineer, with equity participation opportunity. In this role, your work will directly support mission-critical aerospace and defense programs. The successful candidate will: Design and implement advanced ML models (predictive analytics, computer vision, NLP, anomaly detection, reinforcement learning). Analyze large, multi-modal datasets (geospatial, time-series, multi-spectral, sensor data) to generate actionable insights. Develop data processing pipelines and manage MLOps workflows for deployment in both cloud (AWS/Azure/Oracle) and edge environments (avionics, IoT, tactical systems). Create intuitive data visualizations and analytics dashboards (React, Streamlit, or equivalent) to present findings to customers and partners. Apply statistical methods, explainable AI techniques, and best practices in compliance (FedRAMP, NIST 800-171/53, RMF). Work closely with cross-functional teammates (full-stack, DevSecOps, program management) to align AI/ML applications with mission workflows. Have an ownership mindset and strong desire to work in a business with opportunity for leadership and career growth supporting critical national security activities. You’ll be expected to blend technical depth, user-facing design skills, and operational pragmatism, ensuring ML solutions deliver measurable mission outcomes. Knowledge of aerospace standards and cyber-physical system constraints is preferred. You will work closely with cross-functional teammates to deliver secure, resilient, and high-performance systems - and have the long-term opportunity to help build a company of enduring value. Only U.S. persons eligible

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already possessing security clearances will be considered. Native or high-proficiency English communication and cultural knowledge of military/national security environments are required. Responsibilities Lead applied ML research and prototype development for aerospace/defense use cases. Build and optimize models with PyTorch, TensorFlow, Hugging Face, scikit-learn, OpenCV. Implement MLOps best practices: CI/CD, retraining pipelines, monitoring, explainability (XAI). Contribute to front-end visualization and UI/UX design for data products. Support integration of ML into cyber-physical systems in SWaP-constrained contexts (avionics, IoT, flight systems). Collaborate directly with government and industry stakeholders to ensure deliverables meet compliance and mission standards. Support sound business development, solution architecting, and proposal development to ensure offerings are executable with high quality and feasibility at the state of the art. Qualifications U.S. citizen with ability and willingness to obtain a U.S. Government security clearance (Secret or higher). 7+ years' industry experience (10+ preferred) in data science, ML engineering, or applied AI. Proficiency in Python; strong applied ML experience in PyTorch, TensorFlow, Hugging Face, scikit-learn. Background in statistics, data analysis, and visualization (Streamlit, React, D3.js, Tableau, etc.). Flexibility in foundational model use (Anthropic, Hugging Face, Llama, etc.). Hands-on experience across advanced AI/ML techniques such as geospatial analysis, time-series analysis and modeling, anomaly detection, computer vision, NLP, speech-to-text/ASR, OCR, model tuning and adaptations, adversarial systems, PINN, Zero/One/Few shot learning, hyperspectral data processing, etc. 5+ years' experience working with SQL and NoSQL databases. Experience working with industrial production and applications data. Familiarity with MLOps toolchains (Kubeflow, MLflow, DVC, Airflow) and deployments in cloud/edge contexts. Knowledge of DevSecOps pipelines, containerization (Docker/Kubernetes), and secure coding practices. Background or interest in aerospace, aviation, or applied physics domains is preferred. Prior experience at aerospace & defense companies or prior military service is a strong plus. Strong communication in English and cultural fluency in national security environments. Bachelor’s of Science degree required; Master’s/PhD in Data Science, Computer Science, Engineering, Applied Math, or related STEM field strongly preferred.

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