Key Responsibilities

• Design, build, and optimize LLM-based applications with a focus on RAG pipelines
• Develop and integrate retrieval systems (vector databases, embeddings, search engines) with generative models
• Fine-tune and evaluate large language models for specific business use cases
• Collaborate with data scientists, ML engineers, and product teams to deliver production-ready AI solutions
• Implement best practices for model deployment, monitoring, and scaling in cloud environments
• Research emerging AI techniques and apply them to improve performance, accuracy, and efficiency
• Ensure compliance with ethical AI practices, data privacy, and security standards

Requirements

• Multiple years of experience in applied AI/ML engineering
• Strong knowledge of LLMs (e.g., GPT, LLaMA, Mistral) and RAG architectures
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers)
• Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and search technologies
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)
• Solid understanding of NLP concepts: embeddings, tokenization, semantic search
• Strong problem-solving skills and ability to work in fast-paced environments
• Excellent communication skills and collaborative mindset

Nice-to-Have Skills

• Experience with multi-modal AI (text, image, audio)
• Knowledge of MLOps practices and tools (MLflow, Kubeflow)
• Background in knowledge graphs or advanced information retrieval
• Contributions to open-source AI/ML projects

✉ Email: [email protected]

☎ Contact Number: +44(0)1915949744 (1587) / +358 753 266586