AI Engineer

Proven years of experience in MLOps, data engineering, or software development, with a recent focus on GenAI, LLMs, and advanced analytics.

Understanding of software engineering practices such as version control, CI/CD containerisation, and monitoring, particularly within ML or MLOps context.

Proficiency in Python and/or Ruby, with experience in ML libraries (scikit-learn, TensorFlow, PyTorch) and frameworks such as FastAPI, LangChain, or similar.

Hands-on experience with LLM APIs, foundation models, embeddings, vector databases, RAG workflows, and agentic AI systems including MCP.

Experience with large-scale datasets using SQL, distributed data platforms (eg, Spark), and cloud-native infrastructure (eg, AWS, GCP, or on-prem hybrid).

Strong data visualisation and communication skills, with the ability to explain complex models to both technical and non-technical audiences.

Ability to translate ambiguous business problems into structured AI/ML solutions, and to manage multiple projects independently in a fast-paced environment.

Prior experience collaborating with cross-functional teams including data engineers, developers, and UI/UX designers.

B.

S. Degree in Computer Science, Engineering, Statistics, Data Science, or equivalent work experience.