Senior AI/ML Engineer

🕒 Julho 2

⚔️ Virginia – Remoto

⚔️ Virginia – Remote

💵 $150 - $200 / hora

⏳ Contrato/Temporário

🟠 Sênior

🤖 Engenheiro de IA

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Global InfoTek, Inc.

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2001

💼 Consultoria

🎖️ Defesa

📦 Logística

Consulting • Defense • Logistics

A Global InfoTek, Inc. é uma empresa que se especializa em fornecer soluções de segurança nacional de ponta com foco em velocidade, agilidade e inovação. Eles apoiam agências federais fornecendo desenvolvimento de aplicações empresariais, engenharia de nuvem, soluções de cibersegurança, análises avançadas e visualização de dados, assim como inteligência artificial e aprendizado de máquina. Sua missão é equipar a comunidade de segurança nacional com as ferramentas necessárias para combater ameaças e desafios de forma eficaz. A Global InfoTek está comprometida em desenvolver a carreira de profissionais de cibersegurança de alto nível para garantir a segurança do país.

Descrição

• Design, build, and validate machine learning models for RF emitter identification — including feature engineering from sensor data, training pipeline development, model evaluation, and iterative refinement based on results • Conduct hands-on exploratory data analysis on RF sensor datasets using Python and Jupyter notebooks — writing and running analytical code, characterizing feature distributions, identifying data quality issues, and producing documented findings • Implement and maintain ML data pipelines — ingesting NDF sensor streams, applying rollup and preprocessing logic, constructing training datasets, and ensuring pipeline correctness on constrained edge hardware with no cloud dependency • Collaborate with the technical lead and Principal AI/ML Engineer to investigate RF sensor data quality, attribution reliability, and feature behavior under contention — writing code to characterize error sources, validate assumptions, and reproduce findings • Produce clear technical documentation of experiments, model configurations, and results — maintaining reproducibility through disciplined versioning, and contributing to monthly status reports and team knowledge sharing

🎯 Requisitos

• 5+ years of hands-on applied experience in machine learning, data science, or RF signal processing • Demonstrated proficiency in Python for ML and data science work — PyTorch or TensorFlow for model development, Pandas/NumPy for data manipulation, and scikit-learn or similar for evaluation and baseline modeling • Hands-on experience designing, training, and evaluating deep learning models — particularly metric learning, Siamese networks, or other similarity-learning architectures — on real-world, noisy, imbalanced datasets • Practical experience handling real-world data quality problems — missing values, label noise, class imbalance, systematic bias, and sensor artifacts — and the ability to diagnose and address them without discarding valid data • Ability to develop and run ML pipelines on Linux-based systems without cloud infrastructure or GPU acceleration — optimizing for CPU-only inference and multi-threaded data processing on resource-constrained x86 hardware