AI and ML Engineer

Booz Allen Hamilton•Lorton, VA

23d

About The Position

As a programmer, you know that machine learning (ML) is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using 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 warfighter performance. As an ML engineer on our warfighter technology team, you’ll train, test, deploy, and maintain models that learn from data. In this role, you’ll contribute to the direction of mission-critical solutions by applying best-fit ML algorithms and technologies. You’ll grow within a talented team of ML engineers across the company and collaborate with data engineers, data scientists, solutions architects, Mission SMEs, and product owners to deliver world-class solutions to optimize and predict performance. Your skills and technical experience will help your clients navigate the landscape of ML algorithms, tools, and frameworks. Work with us to solve real-world challenges and define ML strategy for warfighter performance. Join us. The world can’t wait.

Requirements

Experience with Python, SQL, Git, and ML frameworks such as PyTorch or TensorFlow
Experience developing computer vision solutions using image processing and numerical computing libraries, building reproducible model training and evaluation workflows, and integrating model inference into analytical or software systems
Knowledge of computer vision and ML methods, including image preprocessing, feature extraction, transfer learning, classification, object detection, segmentation, and visual anomaly detection
Knowledge of neural network architectures and supervised, unsupervised, and self-supervised learning approaches
Knowledge of evaluation practices that address representative dataset design, data leakage, class imbalance, overfitting, and model generalization
Ability to independently translate operational needs into computer vision solutions for defect and anomaly detection, and select modeling approaches appropriate to the available data and constraints
Ability to design validation strategies, establish operating thresholds, and assess performance against acceptance criteria, including tradeoffs between missed defects and false alarms
Ability to obtain a Secret clearance
Bachelor’s degree in CS, Data Science, Engineering, Mathematics, Statistics, AI, or Computer Vision

Nice To Haves

Experience applying computer vision to industrial inspection, manufacturing, materials, textiles, or related quality control applications
Experience working with limited defect samples, limited labeled data, or normal-only training datasets
Experience deploying and monitoring ML models using technologies such as AWS, Docker, CI/CD pipelines, GPU infrastructure, or model-serving platforms
Experience with image-level, pixel-level, and region-level evaluation and the effects of lighting, camera position, scale, orientation, texture, and material variation on inspection performance
Knowledge of specialized visual anomaly detection approaches such as pre-trained feature-based methods, autoencoders, PatchCore, PaDiM, or similar techniques
Ability to design end-to-end visual inspection systems that connect image acquisition, preprocessing, model inference, and downstream applications
Ability to address operational requirements such as throughput, latency, reliability, and ongoing performance monitoring, and adapt solutions to new materials, defect types, or imaging conditions
Secret clearance
Master’s degree in AI, ML, Computer Vision, Data Science, Electrical Engingeering, Computer Engineering, Materials Science, Manufacturing, Applied Analytics, or a related field preferred; Doctorate degree in AI, ML, Computer Vision, Data Science, Electrical Engingeering, Computer Engineering, Materials Science, Manufacturing, Applied Analytics, or a related field a plus
AI, ML, Computer Vision, Data Science, Cloud, DevOps, or Security Certification

Responsibilities

Train, test, deploy, and maintain models that learn from data.
Contribute to the direction of mission-critical solutions by applying best-fit ML algorithms and technologies.
Collaborate with data engineers, data scientists, solutions architects, Mission SMEs, and product owners to deliver world-class solutions to optimize and predict performance.
Help clients navigate the landscape of ML algorithms, tools, and frameworks.
Solve real-world challenges and define ML strategy for warfighter performance.
Deliver maintainable and tested code.
Investigate technical issues.
Clearly communicate findings, limitations, and recommendations to technical and non-technical stakeholders.