Part Time Tensorflow Jobs in Baltimore, MD (NOW HIRING)

Job Description
Remote Work:
No
Job Number:
R0241835
Location:
Fort Meade,MD,US
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AI Model SME
The Opportunity:
As an experienced engineer, you understand that modern mission systems depend on the ability to develop, optimize, and deploy AI/ML models that can operate reliably at scale. Your expertise in analyzing datasets, engineering features, and applying advanced statistical and machine learning techniques will be critical to ensuring model readiness and enhancing real-world operational outcomes. We need your technical depth and problem-solving mindset to advance the development, deployment, and continuous improvement of AI models that directly support evolving mission needs.
As an AI Model SME on our team, you'll design, test, optimize, and operationalize models across cloud, edge, and hybrid environments. You will drive the technical direction for mission-critical AI solutions by selecting best-fit architectures, implementing robust deployment pipelines, and integrating models with enterprise and mission systems. You'll collaborate closely with data engineers, data scientists, cloud and network architects, and ISSE partners to ensure models are supported by secure, scalable infrastructure and high-quality data pipelines. You'll also contribute technical leadership by evaluating emerging AI/ML frameworks, guiding feature engineering approaches, supporting fine-tuning and retraining cycles, and implementing monitoring frameworks to detect performance drift.
Your expertise will help mission partners understand and navigate the rapidly evolving landscape of AI/ML technologies, ensuring deployed models remain performant, reliable, and aligned with operational objectives. Work with us to solve complex real-world challenges and shape the model lifecycle strategy that will drive innovation across mission environments.
Join us. The world can't wait.
You Have:

• 6+ years of experience with engineering
• Experience developing, training, validating, and deploying AI/ML models across cloud, edge, or hybrid environments
• Experience with data preprocessing, feature engineering, and exploratory data analysis
• Experience optimizing AI/ML models including compression, pruning, quantization, and distributed training
• Experience with computing, storage, and networking requirements across model training, tuning, and inference phases
• Knowledge of statistical modeling, machine learning workflows, and model evaluation techniques
• Ability to design and implement model deployment pipelines and MLOps workflows
• Ability to implement monitoring frameworks for detecting model drift, performance degradation, and operational issues
• TS/SCI clearance with a polygraph
• HS diploma or GED

Nice If You Have:

• Experience with distributed compute frameworks such as Ray, Spark, or Horovod for large-scale model training
• Experience with cloud-native AI platforms including AWS Sagemaker, Azure ML, or GCP Vertex AI
• Experience deploying AI/ML models to edge devices or tactical and operational environments
• Experience with common ML frameworks such as PyTorch, TensorFlow, or Scikit-learn
• Experience working in mission-focused or national security environments
• Experience with vector databases, data lakehouse architectures, or streaming data systems
• Experience evaluating new AI model architectures such as LLMs or diffusion models and conducting model benchmarking
• Knowledge of secure AI engineering best practices such as adversarial robustness, model governance, or NIST AI RMF
• Possession of strong programming skills in languages such as Python
• Bachelor's degree

Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with polygraph 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 $99,000.00 to $225,000.00 (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 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.
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