Contract Duration: 10/13/2025 06/30/2026
Work Location: Virtual/Remote until further notice.
When onsite presence is required, work will be performed at one of the following:
- Central Administration Building, 700 South Eisenhower Boulevard, Middletown, PA
- Turnpike Industrial Park, 2850 Turnpike Industrial Drive, Middletown, PA
Interview Type: In-person interviews or work sessions with stakeholders will be conducted onsite in Middletown, PA.
Residency Requirements: PA Preferred, Not Required
Visas Accepted: USC, GC, EAD
Background Check: Enhanced background check required
Job Description: Our client is seeking an Artificial Intelligence Developer to support ongoing initiatives and projects within the Commonwealth.
This role will focus on designing, developing, and implementing AI-based solutions to improve operational efficiency, enhance data-driven decision-making, and support the modernization of enterprise systems.
Responsibilities:
- Develop, train, and deploy AI/ML models to support enterprise use cases
- Collaborate with business and IT teams to identify opportunities for automation and predictive analytics
- Integrate AI solutions into existing systems and workflows
- Perform data preprocessing, feature engineering, and model optimization
- Monitor and maintain deployed models to ensure reliability and accuracy
- Provide technical documentation, reports, and presentations for leadership and stakeholders
- Stay updated with emerging AI/ML technologies, frameworks, and best practices
Required Skills:
- Strong experience with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.)
- Proficiency in programming languages such as Python, R, or Java
- Solid background in data science, statistics, and applied mathematics
- Experience with natural language processing (NLP), computer vision, or predictive modeling
- Knowledge of cloud platforms (AWS, Azure, or GCP) for AI model deployment
- Strong problem-solving and analytical skills
- Excellent communication and documentation abilities
Preferred Skills:
- Experience with large-scale data pipelines and ETL tools
- Familiarity with MLOps practices for model lifecycle management
- Exposure to state or local government IT environments
- Understanding of cybersecurity considerations for AI/ML applications