Applied AI/ML Engineer

Responsibilities

We are representing a confidential federal technology client looking for an Applied AI/ML Engineer to design, build, and deploy production-ready AI solutions. This is a hands-on role focused on turning ambiguous problems into scalable, reliable AI-driven capabilities through modern ML and GenAI techniques.

In this position, you will:

• Design, develop, and deploy machine learning and AI-powered features into production systems
• Apply supervised, unsupervised, and deep learning techniques to structured and unstructured data
• Build and evaluate models for classification, ranking, prediction, NLP, or anomaly detection tasks
• Develop and integrate GenAI solutions including LLM-based workflows, retrieval-augmented generation, and agent systems
• Translate business and user needs into ML problem statements, metrics, and experiments
• Implement data pipelines and feature engineering workflows to support model training and inference
• Evaluate model performance, bias, drift, and reliability; iterate based on results
• Collaborate with software engineers to integrate models into APIs, services, and user-facing applications
• Contribute to architecture decisions around model serving, scalability, and cost optimization
• Document approaches, assumptions, and tradeoffs to support maintainability and knowledge sharing

What We're Looking For

Required qualifications:

• Strong foundation in machine learning concepts including model selection, training, validation, and evaluation
• Experience building and deploying ML models in real-world applications
• Proficiency in Python and common ML libraries (e.g., PyTorch, TensorFlow, scikit-learn)
• Experience working with large language models, embeddings, and prompt-driven systems
• Familiarity with data processing tools and workflows (e.g., Pandas, SQL, Spark, or similar)
• Understanding of software engineering best practices including version control, testing, and code reviews
• Ability to reason about tradeoffs between accuracy, latency, cost, and maintainability
• Strong communication skills and comfort working in cross-functional teams
• Authorization to work in the United States; certain roles may require U.S. citizenship and the ability to obtain and maintain a federal background investigation and/or security clearance

Bonus qualifications:

• Experience working in innovation, R&D, labs, or exploratory engineering teams
• Experience deploying models to cloud platforms and managing inference at scale
• Familiarity with MLOps practices such as model monitoring, CI/CD for ML, and experiment tracking
• Experience contributing to architectural discussions or technical strategy

Location: Hybrid/Remote. Candidates must be located in the DMV area (DC, Maryland, Virginia) and able to participate with in-office collaboration.

How We Work with You

Our talent team at Get A Job.ai partners with leading organizations in the federal technology space. When you apply through our platform, a recruiter will screen your background and qualifications. If there's a strong match, we'll submit your profile to our client for consideration. Please note: do not contact the client directly, as all applications must go through Get A Job.ai to be considered.

Pay

Pay information was not provided for this role. Compensation details will be discussed during the screening process.

Equal Opportunity: Get A Job.ai is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.