Job Description
We are seeking a visionary Generative AI & Search Optimization Engineer to join our elite team. As we prepare for the technological paradigm shift of 2026, we are building the next generation of intelligent search infrastructure that bridges the gap between large language models (LLMs) and semantic web optimization.
In this role, you will not only master advanced AI models but also pioneer how search engines interpret and rank AI-generated content. You will work at the intersection of deep learning, NLP, and SEO strategy to ensure our clients dominate the future of digital discovery.
Why You Should Apply:
- Work on cutting-edge LLM fine-tuning and Retrieval-Augmented Generation (RAG) systems.
- Shape the future of search algorithms in the AI era.
- Competitive compensation and equity packages.
- Flexible remote-first culture with state-of-the-art equipment.
Responsibilities
- Develop and fine-tune large language models (LLMs) specifically optimized for search engine ranking factors.
- Design and implement RAG pipelines to enhance the accuracy and relevance of AI-generated search results.
- Analyze search intent and user behavior to train models on semantic understanding.
- Collaborate with SEO strategists to integrate AI insights into content strategies.
- Optimize codebases for high-performance inference and low latency.
- Stay ahead of industry trends in AI search, including Google's SGE and Bing's AI integration.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field.
- 3+ years of experience in Python, TensorFlow, PyTorch, or Hugging Face.
- Deep understanding of Natural Language Processing (NLP) and Machine Learning algorithms.
- Experience with vector databases (e.g., Pinecone, Milvus, Weaviate).
- Strong grasp of SEO principles and how LLMs impact search visibility.
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.