Generative AI Engineer
7 days ago
Job Overview: We are on the lookout for a Data Scientist with a deep focus on Large Language Models (LLM), General AI, and specialized knowledge in deploying these technologies via APIs using Flask, FastAPI, or Django. This role requires a keen understanding of the latest in AI, including familiarity with Langchain and LlamaIndex for advanced LLM deployment. The ideal candidate will lead our efforts in leveraging LLM for innovative applications, ensuring scalable and efficient model deployment.
Responsibilities:
- Lead the development and deployment of LLM and General AI models, focusing on scalable solutions.
- Specialize in API development for LLM deployment using Flask, FastAPI, or Django, ensuring seamless integration into our products.
- Design, construct, install, test, and maintain highly scalable data management systems, ensuring robust data pipelines for AI deployments.
- Implement data ingestion routines both from within and outside the company, ensuring data quality and accessibility for advanced analytics.
- Demonstrate a deep understanding of Langchain and LlamaIndex for cutting-edge LLM applications.
- Collaborate with product teams and stakeholders to implement AI-driven solutions that meet business needs.
- Stay updated with AI advancements, particularly in LLM and deployment methodologies, to keep our solutions innovative.
Qualifications:
- Expertise in LLM, General AI, and the deployment of AI models.
- Strong experience in API development with Flask, FastAPI, or Django.
- Knowledge of Langchain and LlamaIndex for LLM applications.
- Expertise in AI and ML development tools, frameworks, and libraries (TensorFlow, PyTorch, GPT, etc.).
- Proven ability in data engineering, including managing data pipelines, databases, and real-time data processing systems.
- Proficient in Python and familiar with AI/ML libraries and frameworks.
- Innovative thinker with excellent problem-solving capabilities.
- BSc/BA in Computer Science, Engineering, or related; a graduate degree in a relevant area is highly preferred.
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