Role Summary
This role focuses on developing and deploying AI-driven solutions that enhance automation, data analytics, and operational efficiency for enterprise and government clients. The developer will work closely with architects, data engineers, and DevOps teams to design intelligent systems leveraging modern AI frameworks and scalable infrastructure.

Key Responsibilities

• Design, build, and optimize machine learning models and AI applications for enterprise and government use cases.
• Collaborate with data and infrastructure teams to ensure seamless integration of AI models into production environments.
• Develop APIs, pipelines, and automation frameworks to support continuous training and deployment (MLOps).
• Conduct data preprocessing, feature engineering, and model evaluation to ensure robustness and reliability.
• Implement monitoring and performance-tuning mechanisms for deployed models.
• Research emerging AI technologies and tools to identify opportunities for innovation and efficiency improvements.
• Prepare technical documentation, reports, and presentations for both technical and non-technical audiences.

Requirements

• Strong programming skills in Python and experience with major AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Familiarity with CI/CD and MLOps practices for scalable model deployment.
• Experience with data pipelines, APIs, and microservice architecture.
• Understanding of cloud-based AI services and containerized environments (e.g., Kubernetes, Docker).
• Solid foundation in data structures, algorithms, and applied machine learning.
• Knowledge of NLP, computer vision, or predictive analytics is advantageous.
• Ability to collaborate in multidisciplinary teams and communicate complex technical concepts clearly.