Description:
Fuentes Tech is a fast-growing technology company dedicated to building next-generation web platforms powered by artificial intelligence. We create scalable, intelligent, and secure systems that combine modern web experiences with advanced machine learning infrastructure. Our products include AI-native SaaS tools, real-time analytics engines, and knowledge systems built around large language models (LLMs).
We are hiring a Full Stack Engineer who not only excels at full-stack web development but also has deep expertise in designing, building, and deploying AI/ML models, particularly using PyTorch or TensorFlow. This is not a supporting role: we are looking for someone who can independently drive AI/ML development end-to-end.
Responsibilities
- Build full-stack web applications using Vue.js (Nuxt.js) on the frontend and Express.js/Flask on the backend
- Design scalable REST APIs and backend infrastructure for AI/ML-powered features
- Independently design, implement, and train custom AI/ML models for real-world tasks — including deep learning (NLP, computer vision, etc.)
- Build and optimize LLM-centric solutions, such as:
- Retrieval-Augmented Generation (RAG) systems
- Semantic search and vector database integration (e.g., FAISS, Weaviate, Pinecone)
- Embedding models, fine-tuning, and prompt engineering
- Deploy models into production environments using scalable and reliable workflows
- Work closely with product and engineering teams to design end-to-end intelligent features
- Contribute to architectural decisions, system scalability, and code quality
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- Requirements
- Strong frontend skills in Vue.js/Nuxt.js, including SSR, component-based design, and state management
- Backend proficiency with Node.js (Express.js) and Python (Flask)
- Extensive experience in building and training AI/ML models using PyTorch or TensorFlow
- Strong understanding of deep learning fundamentals (CNNs, RNNs, transformers, etc.)
- Demonstrated experience working with LLMs, including:
- Fine-tuning or adapting transformer-based models (BERT, GPT, LLaMA, etc.)
- Implementing RAG pipelines and working with vector databases
- Strong grasp of data preprocessing, training pipelines, and evaluation metrics
- Familiarity with cloud services (AWS/GCP/Azure), containerization (Docker), and CI/CD practices
- Excellent problem-solving and system design skills
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- Nice to Have
- Experience with LangChain, LlamaIndex, or similar LLM orchestration tools
- Knowledge of MLOps workflows and model monitoring
- Serverless/cloud-native architecture experience
- Contributions to open-source AI/ML libraries or tools