Tactical Machine Learning Engineer

Job Number: R0236159

Tactical Machine Learning Engineer
The Opportunity:

As an experienced engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to c ond uct 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 tactical edge machine learning capabilities. As a machine learning engineer on our tactical edge team, you'll train, test, deploy, and maintain models that learn from data.

In this role, you'll lead the direction of mission-critical solutions by applying best-fit ML algorithms and introducing leading-edge technologies. You'll share your knowledge with a large community of machine learning engineers across the company and collaborate with TAK developers, data scientists, and our tactical experts to deliver world-class solutions to the warfighter combining tactical capability with AI and ML capabilities, reducing their workload and increase their effectiveness on mission. 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 our warfighters.

What You'll Work On:

• Develop and maintain Android applications using Kotlin and Java.
• Integrate ML inference pipelines into production Android apps.
• Deploy and optimize models to run on NPU, GPU, and CPU.
• Perform model quantization, including INT8 or FP16, and size or latency optimization.
• Convert and deploy models from training frameworks to mobile runtimes.
• Profile and tune performance using Android and vendor toolchains.
• Ensure efficient, secure, and reliable on-device AI execution.

Join us. The world can't wait.

You Have:

• 5+ years of experience with Android development
• Experience with Kotlin and Java
• Experience deploying ML models on Android devices
• Experience with TensorFlow Lite, mobile AI SDKs such as Qualcomm QNN, and Android NNAPI or hardware delegates
• Experience with model quantization and mobile optimization
• Experience with debugging and performance profiling
• Knowledge of NPU or GPU acceleration on Android
• Secret clearance
• Bachelor's degree in a Computer Science field

Nice If You Have:

• Experience with Python for model training and conversion
• Experience with PyTorch, TensorFlow, and ONNX
• Experience deploying LLMs, vision, or speech models on mobile
• Experience with pruning, distillation, or quantization-aware training
• Experience with Samsung device optimization
• Experience with ATAK
• Experience in edge or network-denied environments

Clearance:

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

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.

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 $128,700.00 to $292,000.00 (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 application process, 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.

Work Model
Our people-first culture prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely.

• If this position is listed as remote or hybrid, you'll periodically work from a Booz Allen or client site facility.
• If this position is listed as onsite, you'll work with colleagues and clients in person, as needed for the specific 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.