Job Title: GCP RAG Engineer
Location: Hybrid (Atlanta, GA)Job Overview:We are seeking a
GCP RAG Engineer who is experienced in fine-tuning and improving search functions within large-scale systems. The ideal candidate will have a strong background in
Google Cloud Platform (GCP),
Artificial Intelligence (AI) technologies, and
Vertex DB. This role focuses on enhancing search capabilities in complex environments, leveraging cutting-edge AI-driven techniques and GCP tools to ensure seamless search experiences across large datasets.
Key Responsibilities: - Fine-tune and optimize search functions within a large-scale system environment using GCP services.
- Leverage GCP AI tools and Vertex DB to build, test, and deploy models for improving search accuracy and efficiency.
- Work on enhancing retrieval-augmented generation (RAG) models to increase the relevance and precision of search results.
- Collaborate with cross-functional teams, including data scientists, machine learning engineers, and backend developers, to deliver scalable search solutions.
- Utilize data from large-scale databases to continuously improve search algorithms.
- Conduct performance testing, evaluate system bottlenecks, and suggest improvements.
- Stay up-to-date with the latest AI and search engine optimization techniques and integrate them into the GCP architecture.
- Provide technical expertise in developing innovative solutions using Google Cloud AI/Client products.
Required Qualifications: - 5+ years of experience working with Google Cloud Platform (GCP), including AI/Client services and Vertex DB.
- Strong knowledge of retrieval-augmented generation (RAG) and experience in enhancing search models at scale.
- Expertise in large-scale search systems, with a proven track record of improving search functionalities and performance.
- Proficiency in Python, TensorFlow, or other machine learning frameworks.
- Experience with GCP AI services, such as BigQuery, Cloud AI APIs, Vertex AI, and other relevant tools.
- Hands-on experience in developing and fine-tuning machine learning models for search algorithms.
- Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
Preferred Qualifications: - Experience working with natural language processing (NLP), search ranking models, and information retrieval systems.
- Knowledge of distributed systems, big data frameworks, and handling massive datasets efficiently.
- Familiarity with AI-driven search optimizations and cloud infrastructure management.
- Prior experience working in an Agile environment.
