Machine Learning Research Engineer

Machine Learning Research Engineer The Opportunity: As an experienced engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using Machine Learning (ML) techniques makes you an integral part of delivering a customer-focused solution. We need your technical knowledge and desire to problem-solve to support the creation of physics-aware foundational models for remote sensing applications. As a machine learning engineer on our national security team, you’ll train, test, deploy, and maintain models that learn from data. In this role, you’ll own and define the direction of mission-critical solutions by applying best-fit ML algorithms and technologies. You’ll be part of a large community of machine learning engineers across the company and collaborate with data engineers, data scientists, solutions architects, and remote sensing scientists to deliver world class solutions to turn a detailed technical design into a stable, high-performing, well-evaluated PyTorch system. You will work across self-supervised pretraining, lab-to-scene alignment, multi-task model training, uncertainty calibration, benchmarking, and release readiness. This role is ideal for someone who can bridge model research and production-grade ML engineering. Your skills and extensive technical expertise will guide clients as they navigate the landscape of ML algorithms, tools, and frameworks. Work with us to solve real-world challenges and define ML strategy for applied remote sensing. Join us. The world can’t wait. You Have: 4+ years of experience with ML engineering, research engineering, or applied ML development Experience with PyTorch, including building and training deep learning models Experience with transformer-based models, self-supervised learning, multi-task learning, or large-scale training pipelines Experience with debugging model training issues such as instability, memory bottlenecks, dataloader performance, and reproducibility Experience with software engineering fundamentals, including testing, code review, and maintainable ML workflows Top Secret clearance Bachelor’s degree Nice If You Have: Experience with computer vision, scientific imaging, remote sensing, or hyperspectral data Experience with masked autoencoders, contrastive learning, retrieval models, or multimodal alignment Experience with uncertainty estimation, calibration, conformal prediction, or OOD detection Experience with distributed training, mixed precision, and GPU performance optimization Experience supporting model evaluation and qualification in high-stakes or research-heavy domains TS/SCI clearance Master’s degree in Computer Science, Machine Learning, Applied Mathematics, Physics, Remote Sensing, or a related field preferred; Doctorate degree in Computer Science, Machine Learning, Applied Mathematics, Physics, Remote Sensing, or a related field a plus Clearance: Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; Top Secret clearance is required. 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Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date. Identity Statement As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud. 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