As an experienced Machine Learning Research Engineer on our national security team, you will play a pivotal role in developing physics-aware foundational models for remote sensing applications. Your daily tasks include training, testing, deploying, and maintaining ML models that process large datasets, collaborating closely with data engineers, scientists, and solutions architects to ensure the stability and performance of PyTorch systems. You will work on self-supervised pretraining, lab-to-scene alignment, multi-task model training, uncertainty calibration, benchmarking, and release readiness. Ideal candidates have 4+ years of ML engineering experience, proficiency in PyTorch, transformer-based models, and software engineering fundamentals such as testing and code review. Experience with computer vision, remote sensing data, distributed training, and GPU optimization is a plus, making you well-equipped to tackle complex challenges in the field of applied remote sensing.
Design and implement machine learning models using PyTorch for remote sensing applications.
Train, test, deploy, and maintain ML models to ensure high performance and stability.
Collaborate with data scientists and engineers to develop physics-aware foundational models.
Debug model training issues related to instability, memory bottlenecks, and dataloader performance.
Optimize GPU performance and implement distributed training for large-scale pipelines.
Conduct benchmarking and uncertainty calibration for released ML systems.
What we're looking for
4+ years of experience in ML engineering, research, or applied development.
Proficient in PyTorch for building and training deep learning models.
Experience with transformer-based models, self-supervised learning, and multi-task learning.
Expertise in debugging model training issues related to instability, memory bottlenecks, and reproducibility.
Strong background in software engineering practices including testing and code review.
Bachelor’s degree in Computer Science, Machine Learning, Applied Mathematics, Physics, or Remote Sensing.
Market check
Salary context
This
$99,000–$225,000
range sits above
35%
of similar postings on FindRole.
Peer median band
$150,000–$230,050
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$147,358–$234,150
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Booz Allen Hamilton
Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting
Booz Allen Hamilton currently has
629 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 616 roles with salary data.
Python
TensorFlow
PyTorch
scikit-learn
MATLAB
C++
signal processing
wireless communication
MIMO
OFDM
SDRs
GPU acceleration
embedded machine learning
real-time systems
adaptive modulation
beamforming
cognitive radio techniques
3GPP
IEEE 802.11/15
military waveforms