Build and optimise the production machine learning systems that power enterprise agentic AI.
You will work on the core ML components that sit inside production AI deployments — from fine-tuning and evaluation pipelines to inference optimisation and model serving. You will work closely with AI Architects and Data Platform Engineers to bring models from experiment to production reliably.
What you'll do
- Build, evaluate, and deploy machine learning models in production environments
- Develop fine-tuning and RLHF pipelines for enterprise LLM use cases
- Optimise model inference for latency, throughput, and cost
- Build evaluation frameworks and monitoring for production model behaviour
- Collaborate with architects on agentic system design
What we're looking for
- Strong ML engineering background with production deployment experience
- Proficiency in Python; experience with PyTorch, HuggingFace, or similar
- Experience with LLMs, fine-tuning, and evaluation methodologies
- MLOps mindset — comfortable with CI/CD for models and reproducibility