Job Title : AI / NLP Engineer / Developer
Location : Remote (Ohio, USA)
Employment Type : Contract, Long Term
Prior experience with Cardinal is highly preferred.
Job Overview : We are seeking an experienced AI / NLP Engineer to design, develop, and integrate advanced AI solutions leveraging Azure Cognitive Services , Large Language Models (LLMs) , and NLP frameworks . The ideal candidate will have hands-on experience with Databricks , SQL Server , and modern AI / ML pipelines , capable of building intelligent, scalable, and production-ready solutions.
Key Responsibilities :
- Design and implement AI and NLP-based solutions integrated with Azure Cognitive Services and Databricks .
- Develop, fine-tune, and deploy LLMs and NLP models using frameworks like PyTorch , LangChain , and OpenAI APIs .
- Work with offline open-weight models and integrate them within enterprise data workflows.
- Implement Claude API , OpenAI API , and other third-party model integrations for conversational and generative AI use cases.
- Architect and automate data engineering pipelines to support ML / AI workloads.
- Integrate Databricks Foundational Models into enterprise data ecosystems for model training, inference, and monitoring.
- Collaborate with data scientists, engineers, and architects to ensure model scalability, performance, and compliance.
- Monitor and optimize model performance and implement retraining strategies as needed.
Must-Have Skills :
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.Overall IT Experience : 8-12 YearsExpertise in Python and NLP model development (Transformers, LLMs, etc.).Strong experience with Azure Cognitive Services integration .Hands-on experience with Databricks and SQL Server .Experience with Offline Open Weight Models and Databricks Foundational Model Integration .Proficiency in Claude API , OpenAI API , LangChain , and PyTorch .Knowledge of AI / ML architecture and data pipeline design for scalable solutions.Nice-to-Have Skills :
Experience with Vector Databases (FAISS, Pinecone, etc.) .Familiarity with MLOps , Model Monitoring , and LLM fine-tuning .Exposure to Azure Machine Learning , Kubernetes , and Docker for deployment.Understanding of Responsible AI principles, model governance, and security.