AI Engineer

5 days ago

Metro Manila Philippines Ibex Staffing Solutions Full time

We are seeking a highly skilled AI Engineer to design and develop intelligent, adaptive systems that learn from real-world customer interactions. This role focuses on building AI‑driven agents, reinforcement learning pipelines, and continuous feedback loops that enhance user experience and expand product intelligence over time. Key Responsibilities Design, develop, and deploy AI agents capable of autonomous decision‑making and natural interaction with customers. Build reinforcement learning and feedback loops to train models using customer behavior and conversation outcomes. Integrate AI systems with customer‑facing applications such as chatbots, voice assistants, and recommendation engines. Implement pipelines for continuous model evaluation, optimization, and monitoring in production. Develop and manage data ingestion and preprocessing systems for customer interaction logs. Work with LLMs, NLP models, and retrieval‑augmented generation (RAG) systems to improve contextual understanding. Ensure compliance with data privacy, ethical AI standards, and model governance requirements. Research and prototype emerging AI techniques to improve adaptivity, reasoning, and learning efficiency. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, or related field. 3+ years of experience in applied AI/ML engineering, ideally with production‑grade systems. Proficiency in Python and frameworks such as PyTorch, TensorFlow, or LangChain. Experience with LLM fine‑tuning, reinforcement learning, or feedback‑based learning systems. Familiarity with vector databases (Pinecone, Weaviate, FAISS) and knowledge graph concepts. Experience deploying models with Docker, Kubernetes, or cloud platforms (AWS/GCP). Strong understanding of conversational AI, NLP, and retrieval systems. Preferred Qualifications Experience building autonomous or semi‑autonomous agents using APIs and tool‑use frameworks. Background in human‑in‑the‑loop or active learning systems. Knowledge of prompt engineering, context management, and RLHF. Familiarity with evaluation frameworks for LLMs and conversational agents. #J-18808-Ljbffr

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