- Develop, test, and deploy advanced AI/ML models and algorithms using Python.
- Design and implement prompt engineering techniques to optimize model responses and performance.
- Collaborate with cross‑functional teams to integrate AI solutions into existing systems and workflows.
- Utilize AI agentic frameworks to create intelligent systems capable of autonomous decision‑making.
- Work with large language models (LLMs) to develop applications that understand and generate human‑like text.
- Implement retrieval‑augmented generation (RAG) strategies to enhance the context and relevance of generated outputs.
- Manage and optimize vector databases for efficient storage and retrieval of data used in AI applications.
- Conduct research and stay up‑to‑date with the latest advancements in AI/ML technologies and methodologies.
- Document processes, models, and methodologies for future reference and knowledge sharing.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Proven experience in advanced Python programming,
with a solid understanding of data structures and algorithms.
- Demonstrated expertise in prompt engineering and its application within AI models.
- Familiarity with AI agentic frameworks and their implementation in real‑world applications.
- Experience working with large language models (LLMs) and understanding their architecture and functionalities.
- Knowledge of retrieval‑augmented generation (RAG) techniques and vector databases.
- Ability to work effectively in a collaborative environment and communicate complex concepts to non‑technical stakeholders.
- Strong analytical and problem‑solving skills with a focus on delivering high‑quality results.
Preferred, but not required
- Experience with frameworks and libraries such as TensorFlow, PyTorch, or Hugging Face.
- Familiarity with cloud platforms (AWS, Azure, Google Cloud) and their AI/ML services.
- Knowledge of data preprocessing and data engineering practices.