
Chief AI Technology Officer
10 hours ago
We are seeking a seasoned professional to join our team as a Senior AI Engineer specializing in the development and optimization of Large Language Models (LLMs). The ideal candidate will have hands-on experience in deploying, fine-tuning, and integrating LLMs with Retrieval-Augmented Generation (RAG) architectures to enhance the efficiency and accuracy of AI-powered solutions.
Key Responsibilities:
- Design, develop, and optimize AI solutions using LLMs (e.g., GPT-4, LLaMA, Falcon) and RAG frameworks.
- Implement and fine-tune models to improve response relevance and contextual accuracy.
- Develop pipelines for data retrieval, indexing, and augmentation to improve knowledge grounding.
- Work with vector databases (e.g., Pinecone, FAISS, Weaviate) to enhance retrieval capabilities.
- Integrate AI models with enterprise applications and APIs.
- Optimize model inference for performance and scalability.
- Collaborate with data scientists, ML engineers, and software developers to align AI models with business objectives.
- Ensure ethical AI implementation, addressing bias, explainability, and data security.
Requirements:
- 8+ years of experience in software development according to industry standards;
- Strong experience in training and deploying LLMs using frameworks like Hugging Face Transformers, OpenAI API, or LangChain.
- Proficiency in Retrieval-Augmented Generation (RAG) techniques and vector search methodologies.
- Hands-on experience with vector databases such as FAISS, Pinecone, ChromaDB, or Weaviate.
- Solid understanding of NLP, deep learning, and transformer architectures.
- Proficiency in Python and ML libraries (TensorFlow, PyTorch, LangChain, etc.).
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps workflows.
- Familiarity with containerization (Docker, Kubernetes) for scalable AI deployments.
- Strong problem-solving and debugging skills.
- Excellent communication and teamwork abilities.
What We Offer:
- A competitive compensation package.
- A supportive team environment.
- Flexible work arrangements.
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