AI Developer

We are seeking an experienced AI Developer to design, build, and optimize scalable Artificial Intelligence solutions. You will work closely with cross-functional teams to deploy machine learning models, NLP systems, and advanced analytics capabilities into enterprise applications.

• Location: Raleigh, NC (Local candidates only)
• Work Arrangement: Hybrid
• Interview Mode: Webcam or In-Person

• AI & ML Development: Design, test, and deploy machine learning algorithms, predictive models, NLP systems, and computer vision applications.
• Data Engineering: Collect, cleanse, and preprocess large structured and unstructured datasets for feature engineering and model training.
• Performance Optimization: Monitor deployed models, improve accuracy, eliminate bottlenecks, and implement best practices for version control and debugging.
• Collaboration & Innovation: Translate business needs into AI solutions, support proof-of-concept (POC) projects, and stay updated on emerging AI frameworks.

To excel in this role, you must bring a strong blend of the following technical and programming skills:

• Machine Learning & AI Frameworks: Proven experience developing and deploying core machine learning algorithms and AI models.
• Advanced AI Technologies: Strong understanding of Natural Language Processing (NLP), predictive analytics, or computer vision.
• Data Processing: Experience analyzing and engineering large-scale datasets while ensuring data quality and compliance.
• Software Development: Excellent programming skills with an understanding of model deployment, testing, and monitoring lifecycle techniques.
• Problem-Solving: Strong analytical and communication skills to effectively collaborate across diverse technical groups.

• Public Sector / Government Experience (Required)
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with major cloud infrastructure (
  AWS, Azure, or GCP
  ).
• Familiarity with MLOps, Dev Ops
  , and distributed computing environments.
• Knowledge of Responsible AI, governance, and model explainability.