Senior MLOps Engineer - AWS AI Platform (Contract - 6 Months)London, United KingdomJuly 15, 2026ContractApply Now### Job DescriptionLocation: London, UK Work Model: On-site Contract Duration: 6 MonthsWe are looking for a Senior MLOps Engineer with strong experience in machine learning infrastructure and AWS AI services to join our client’s on-site team in London on a 6-month contract.This project focuses on productionising multiple Generative AI and Machine Learning solutions by designing a scalable MLOps platform, implementing automated deployment pipelines, and establishing governance and monitoring standards for enterprise AI systems.—## Project ObjectivesDuring this engagement, you will:* Build an enterprise MLOps platform on AWS* Deploy production-ready LLM applications* Implement automated model deployment pipelines* Build AI monitoring and governance capabilities* Standardise the ML lifecycle across multiple engineering teams* Deliver operational

documentation and knowledge transfer—## What You’ll Do### AWS AI Platform* Design and build an enterprise MLOps platform using Amazon SageMaker* Develop reusable infrastructure supporting model training, validation and deployment* Configure SageMaker Pipelines and Model Registry* Deploy scalable inference endpoints using SageMaker Endpoints### LLM Infrastructure* Deploy containerised AI workloads on Amazon EKS* Build Retrieval-Augmented Generation (RAG) pipelines* Integrate vector databases including Pinecone and Amazon OpenSearch Vector Engine* Optimise GPU workloads for low-latency inference### ML CI/CD* Build CI/CD pipelines for machine learning using GitHub Actions* Automate model testing, validation, deployment and rollback* Implement model versioning and artifact management* Standardise deployment workflows across engineering teams### Monitoring & AI Operations* Monitor model performance, latency and drift* Implement observability using Amazon CloudWatch, Grafana, MLflow and LangSmith* Build dashboards for production AI services* Support incident management and model performance optimisation### Governance* Implement reproducible ML workflows* Establish approval processes for production models* Support AI governance, traceability and auditability* Produce operational documentation and deployment standards—## What We’re Looking For### Required Skills & Experience* 5+ years of experience in MLOps or Machine Learning Engineering* Strong experience with AWS AI services including: + Amazon SageMaker + Amazon EKS + IAM + CloudWatch + S3* Strong Kubernetes administration* Python* Docker* Terraform* GitHub Actions* MLflow* LangChain* LangSmith* Experience deploying LLMs in production* Experience with vector databases* Strong understanding of RAG architectures* Excellent English communication skills—### Nice to Have* Amazon Bedrock* Hugging Face* NVIDIA Triton Inference Server* KServe* Kubeflow* Pinecone* OpenSearch Vector Engine* AWS Machine Learning Specialty Certification—## Project Deliverables* Production-ready Amazon SageMaker platform* Enterprise MLOps framework* Automated ML deployment pipelines* LLM inference platform* AI monitoring dashboards* Governance documentation* Knowledge transfer to internal engineering teams—Location: London, UK Work Model: On-site Contract Duration: 6 Months #J-18808-Ljbffr