The Opportunity: 

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. 

You Have:  

• 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 deliver maintainable and tested code, investigate technical issues, and clearly communicate findings, limitations, and recommendations to technical and non-technical stakeholders
• Ability to obtain a Secret clearance
• Bachelor’s degree in CS, Data Science, Engineering, Mathematics, Statistics, AI, or Computer Vision

Nice If You Have:  

• 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

Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

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.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.

Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

• Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.

• Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.

• Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.