AI Engineer Consultant Digital Innovation

What you'll work on

• Work closely with T&L SMEs to build a deep understanding of business/client challenges and document detailed project requirements.
• Support the design, development, documentation and technical delivery of advanced analytics, automation, and AI solutions to streamline repetitive business tasks intelligently.
• Process, clean and verify the integrity of data used for analysis in a project and, where necessary, identify and proactively source additional data.
• Perform analysis on complex datasets using a variety of techniques, visualise and present results in a clear, logical manner to both technical and non-technical stakeholders.
• Support the data science team in building and maintaining code in-house and on the cloud
• Proactive ideation of novel AI engineering and automation solutions in line with business requirements and project pipelines
• Take data science solutions from proof of concept, through to a full production system.
• Create, monitor and troubleshoot API’s.
• Must be a team player and work collaboratively with the business and the team.

*Connect to your skills and professional experience

Essential:**

• Experience full-stack software or ML engineering with strong Python Development practices (CI/CD, testing, muti-threading/asynchronous execution, PEP8 etc.)
• Experience designing, testing and deploying production-scale AI/ML solutions (APIs, microservices, cloud deployment, endpoint deployment, registries, pipelines)
• Experience with LLM based applications (NLP, embeddings, semantic search, RAG, Graph RAG, fine-tuning)
• Proficient in ML tools and modern ecosystem (PyTorch, MLFlow, FastAPI, SQL Alchemy)
• Experience retrieving data from structured, unstructured and web sources (Selenium/PlayWright, Pandas, XML etc)
• Experience in Azure including Azure Fabric, Data Factory and Azure integrated services such as ML Studio, Foundry, Synapse, Cosmos
• Aware of advances in the AI ecosystem and eager to explore, develop and deploy novel cutting-edge solutions.
• Experience leading end-to-end data client projects, from POC development to production/cloud environment.
• Evidence of deployment of GenAI/ML models in production systems with good grasp of data engineering lifecycles, ML Ops and LLM Ops.