Job Description

Remote Work:
Yes
Job Number:
R0203925
Location:
Alexandria,VA,US
Embedded ML Developer

Key Role:

Perform as a member in our elite Digital Battlespace Platform (DBP) team to build next generation technologies for our defense clients leading our materials and science engineering efforts. Perform as an Artificial Intelligence (AI) and Machine Learning (ML) Engineer and process data and information at massive scale with machine learning technologies. Apply leading-edge principles, theories, and concepts and contribute to the development of new principles and concepts. Work on unusually complex problems and provide highly innovative solutions.

Basic Qualifications:

  • 3+ years of experience with developing, training, testing, and integrating AI and ML models

  • Experience with developing and testing AI/ML models for low size, weight, and power (SWAP), and small form factor edge devices, such as Qualcomm Snapdragon, Nvidia Jetson Xavier/Orin, or Raspberry Pi

  • Experience with Docker

  • Experience with custom tools, including Python, Shell Scripting, SQL, and Cloud storage tools

  • Experience with using deep learning frameworks, including Keras, TensorFlow lite, Onnx, or PyTorch mobile

  • Experience with optimizing and compressing AI/ML models for small form factor edge compute devices, including quantization or pruning

  • Experience with creating benchmark datasets and Python packages to facilitate data science objectives

  • Experience in integrating ML models with sensor platforms

  • Secret clearance

  • HS diploma or GED

Additional Qualifications:

  • Experience with DoD

  • Experience with implementing machine learning pipelines using TensorFlow, Numpy, Scikit-Learn, OpenCV, DVC, W&B, TFLite, SNIPE, SHAP, UMAP, or ART

  • Experience with deploying k3s to bare metal hardware

  • Experience with conducting research and the implementation of the latest advancements in machine learning to analyze and process large-scale spatio-temporal data

  • Ability to work with clients to deploy machine learning systems within existing networks using virtual machines or containerization

  • Possession of excellent analytical and problem-solving skills in highly complex environments

  • Master’s degree in Engineering, Computer Science, or Data Science

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 $96,600.00 to $220,000.00 (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.

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.

EEO Commitment

We’re an equal employment opportunity/affirmative action employer that empowers our people to fearlessly drive change – no matter their race, color, ethnicity, religion, sex (including pregnancy, childbirth, lactation, or related medical conditions), national origin, ancestry, age, marital status, sexual orientation, gender identity and expression, disability, veteran status, military or uniformed service member status, genetic information, or any other status protected by applicable federal, state, local, or international law.

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