At a Glance
- Tasks: Build and optimise cutting-edge machine learning pipelines using AWS and Python.
- Company: Join a forward-thinking tech company in the heart of London.
- Benefits: Competitive daily rate, flexible contract, and opportunities for skill enhancement.
- Other info: Dynamic role with potential for career advancement in a vibrant tech environment.
- Why this job: Make an impact with innovative ML solutions and work on exciting projects.
- Qualifications: Experience in machine learning, Python, and AWS tools is essential.
The predicted salary is between 60000 - 80000 £ per year.
Location: London, UK — Contract. Daily rate: 500-600 GBP.
Description:
- AWS ML stack: SageMaker (training, fine-tuning, endpoints), Bedrock (foundation models, embeddings, agents), Step Functions, Lambda, S3, DynamoDB.
- Build production ML end-to-end pipelines; fine-tune models (LoRA, PEFT); evaluate and monitor models with MLOps practices (model registry, CI/CD, monitoring, drift detection).
- Work on RAG and embeddings: vector databases (OpenSearch Serverless, FAISS), chunking strategies, retrieval evaluation, knowledge-base architectures.
- Develop in Python and apply ML frameworks (PyTorch, HuggingFace Transformers) and data tooling (pandas, NumPy, PySpark).
- Explore spatial/geometric ML for constraint optimization, generative and parametric design, layout algorithms, spatial reasoning.
- Integrate LLMs: prompt engineering, function calling, agentic architectures, NLP for domain-specific tasks such as code compliance and design narration.
- Apply software engineering fundamentals: APIs, containerisation (ECS/Docker), IaC (CDK or CloudFormation), CI/CD.
Skills:
- AWS
- Python
- Machine learning
- MLOps
- LLM
- PySpark
- RAG
- CI/CD
- NLP
- API
- Docker
- Cloud formation
We think you need these skills to ace Machine Learning Engineer in London
AWS ML stack
SageMaker
Bedrock
Step Functions
Lambda
S3
DynamoDB
