Salary: £60,000 - 80,000 per year Requirements:
* Strong Python and experience with TensorFlow, PyTorch or scikit-learn
* Hands-on LLM work—prompt engineering, modern NLP techniques
* AWS experience: SageMaker, Bedrock, S3, Lambda, CloudWatch
* Understanding of deep learning, transformers and attention mechanisms
* Knowledge of RAG systems, vector databases and embeddings
* Experience deploying ML models to production and monitoring them
* Familiarity with Docker, CI/CD and experiment tracking
* Solid stats background, model evaluation and feature engineering
* Good communication skills and ability to work cross-functionally
* Bonus points for:
* LLM fine-tuning and frameworks like LangChain, Hugging Face or LlamaIndex
* Semantic search, recommendation engines, time-series or computer vision
* IaC tools like Terraform or CloudFormation
* Real-time inference, distributed training or large-scale optimisation
* Cloud or ML certifications
Responsibilities:
* Building and deploying ML models and LLM applications
* Fine-tuning large language models for specific use cases
* Working with prompt engineering and RAG systems
* Creating end-to-end ML pipelines—injection, feature engineering, deployment
* Developing LLM-powered tools: chatbots, automation, content generation
* Implementing MLOps practices: versioning, experiment tracking, CI/CD, monitoring
* Optimising for performance, scalability and cost in the cloud
* Integrating vector databases, embeddings and semantic search
* Collaborating with engineering, data and product teams
Technologies:
* AI
* AWS
* Lambda
* CI/CD
* Cloud
* CloudWatch
* Computer Vision
* Docker
* LLM
* Machine Learning
* PyTorch
* Python
* TensorFlow
* Terraform
More:
We are a fast-growing tech company based in Bristol, seeking an AI / ML Engineer to help build and deploy cutting-edge machine learning and LLM solutions. With our hybrid work model, youll spend 3 days in the Bristol office and 2 days working remotely, enjoying a competitive salary of £60,000 to £80,000 along with benefits including private medical and dental coverage. Youll join a dynamic engineering and data team, where you will have the opportunity to influence our MLOps practices and model deployment strategies while focusing on your professional development.
last updated 50 week of 2025