java with generative ai engineer
| Key Qualifications: – Proficiency in Python programming. – Expertise in Langchain for advanced API interactions and large-scale data processing. – In-depth knowledge of Hugging Face’s transformer models and libraries. – Experience in developing and deploying applications with FastAPI. – Specialized understanding of Generative Large Language Models (LLMs) and their applications. Responsibilities: Generative AI/ML & LLM Expertise: – Employ Langchain for sophisticated API interactions and to process large datasets. – Interpret flowcharts to understand and design AI-driven workflows. – Integrate Hugging Face and other generative AI models into various applications. – Apply concepts of Chain of Thought (COT), Tree of Thought (TOT), and ReAct (Response & Act) agents in generative tasks. – Understand and implement machine learning and generative modeling techniques! – Utilize different prompting strategies to effectively communicate with generative AI models. – Develop causal inference models to understand data relationships and generate predictive insights. – Leverage LLMs for analyzing log data, code review, correction, and generation. – Extract insights from structured data sources like Excel, BigQuery, and SQL using generative models. – Integrate LLMs into API functions for enhanced interactivity and automation in tasks such as form-filling. – Expose models like LLama2 as APIs for broader application use. – Ensure the security and integrity of prompts and input data in generative AI applications. Python Development: – Establish connections to diverse data sources using Python. – Construct robust APIs with Python and FastAPI. – Utilize data processing libraries such as NLTK and Pandas for pre-processing tasks. – Develop graph and clustering models to understand complex data relationships. – Package code for deployment, ensuring it is optimized for production environments. Google Cloud Platform (GCP) Expertise: – Manage GCP services including BigQuery, Cloud Functions, Vertex AI, Model Garden, and GCS buckets. – Deploy and orchestrate containerized applications with Docker and Google Kubernetes Engine (GKE). – Design, implement, and maintain data workflows with Airflow pipelines and Scheduler. – Establish monitoring and alerting systems to maintain high availability and performance. – Administer IAM roles and permissions to ensure secure cloud operations. Candidate Profile: The ideal candidate will be a forward-thinking and innovative Generative AI Engineer with a robust background in Python and generative AI/ML technologies. You should be proficient in managing and interpreting large-scale data with Langchain, integrating cutting-edge generative models, and have a nuanced understanding of LLM applications. Your experience with GCP will be crucial for deploying and managing generative AI solutions in the cloud effectively. Your role will be central to the development of AI-driven generative applications, ensuring they are innovative, scalable, and secure. |