We are looking for an AI Engineer.

Responsibilities:

• Develop and optimize AI-driven solutions: Design, implement, and refine AI systems that leverage Retrieval-Augmented Generation (RAG), embeddings, and multi-model architectures to solve complex business challenges.
• Integrate and deploy multi-modal AI models: Work with multi-modal AI models (text, image, etc.) and tools like LangChain, LangGraph, and LlamaIndex to create comprehensive solutions that meet diverse user needs.
• Conduct prompt engineering: Design, test, and refine prompts to enhance the performance and reliability of AI models in various applications, ensuring they deliver accurate and contextually relevant results, implement evaluations for the prompts.
• Leverage creative AI tools: Utilize and integrate AI tools such as MidJourney and Stable Diffusion for generating and enhancing visual content, supporting diverse AI-driven projects.
• Optimize model performance: Apply advanced techniques such as embeddings, transfer learning, and the use of specialized tools to fine-tune models, improving their accuracy, efficiency, and scalability.
• Stay updated on AI advancements: Continuously monitor and assess the latest trends, tools, and research in AI, particularly in areas like RAG, embeddings, multi-models, and tools like LangChain, LangGraph, and LlamaIndex, to incorporate cutting-edge techniques into projects.
• Ensure ethical AI deployment: Implement best practices in AI ethics, ensuring models are fair, transparent, and free from biases that could negatively impact users.
• Document and communicate AI solutions: Clearly document the design, implementation, and optimization of AI systems, and effectively communicate these to technical and non-technical stakeholders.
• Troubleshoot and refine AI systems: Identify and resolve issues in AI models and pipelines, ensuring robust performance across different scenarios and applications.

Requirements:

• Hands-on experience in AI/ML development.
• Proficiency in programming languages such as Python, TensorFlow, PyTorch, or other relevant frameworks.
• Strong knowledge of AI/ML algorithms and architectures, particularly in multi-modal and retrieval-augmented generation models.
• Experience with AI deployment and integration into production systems.
• Familiarity with AI ethics, including fairness, transparency, and bias mitigation strategies.
• Strong troubleshooting skills with the ability to identify and resolve issues in AI models and pipelines.
• Proven experience in developing and optimizing AI systems, specifically using Retrieval-Augmented Generation (RAG), embeddings, and multi-modal architectures.
• Experience with multi-modal AI models (e.g., text, image) and proficiency in tools like LangChain, LangGraph, and LlamaIndex.
• Demonstrated experience in prompt engineering, including designing, testing, and refining prompts.
• Experience with creative AI tools such as MidJourney and Stable Diffusion for visual content generation.
• Strong experience in model optimization techniques, including embeddings, transfer learning, and fine-tuning models for performance improvements.