ob Summary :
We are seeking a highly skilled AI Applied Engineer to design, develop, and implement innovative digital solutions powered by Artificial Intelligence. The ideal candidate will bridge the gap between data science and engineering-transforming AI models into scalable, production-ready applications that deliver real-world business impact.
Key Responsibilities :
Design, develop, and deploy AI and Machine Learning (ML) solutions for digital transformation initiatives.
Collaborate with data scientists to operationalize AI models using MLOps best practices.
Integrate AI-driven components into existing enterprise systems and cloud platforms.
Build scalable data pipelines to support model training, testing, and deployment.
Leverage frameworks such as TensorFlow, PyTorch, or Scikit-learn for model development and optimization.
Work with cloud-based AI services (Azure AI, AWS SageMaker, Google Vertex AI, etc.) for large-scale deployments.
Apply Natural Language Processing (NLP) , Computer Vision , and Predictive Analytics techniques to solve complex business challenges.
Partner with cross-functional teams to identify opportunities for AI automation and digital innovation .
Ensure solutions meet performance, scalability, and ethical AI standards.
Maintain detailed technical documentation , conduct code reviews, and mentor junior engineers.
Required Skills & Qualifications :
Strong programming skills in Python , Java , or C# .
Hands-on experience with AI / ML frameworks (TensorFlow, PyTorch, Keras, Scikit-learn).
Experience deploying AI models into production environments .
Knowledge of MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).
Familiarity with data engineering tools and ETL pipelines.
Understanding of cloud platforms (Azure, AWS, or GCP) and their AI / ML services.
Proven experience in digital transformation or intelligent automation projects.
Strong analytical and problem-solving abilities with a focus on innovation.
Excellent collaboration and communication skills.
Nice to Have :
Experience in Generative AI (LLMs, Prompt Engineering, LangChain, RAG frameworks) .
Exposure to Edge AI , IoT , or Real-time analytics .
Familiarity with API integration and microservices architecture .
Knowledge of Responsible AI principles and model governance.
Education :
Bachelor's or Master's degree in Computer Science , Artificial Intelligence , Data Science , or a related technical field.
Ai Engineer • Louisville, KY, Kentucky, USA