Senior MLOps Engineer: AWS AI Platform (On-site London)

Talenzon group; Greater London; On-site; GBP 140,000 - 210,000; Full time

Job summary

Talenzon group is seeking a Senior MLOps Engineer to join our London-based on-site team for a 6-month contract. You will design and implement an enterprise MLOps platform on AWS, deploy production-ready LLM applications and automate model deployment pipelines.

You will build AI monitoring, governance, and CI/CD workflows, plus standardize the ML lifecycle across teams. Strong English communication and hands-on experience with SageMaker, EKS, and vector databases are required.

Qualifications

• 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 and with vector databases.
• Understanding of RAG architectures and English communication skills.

Responsibilities

• Design and build an enterprise MLOps platform on AWS.
• Develop reusable infrastructure supporting model training, validation and deployment.
• Configure SageMaker Pipelines and Model Registry; deploy scalable endpoints.
• Build CI/CD pipelines for ML using GitHub Actions and automate testing, deployment and rollback.
• Establish governance, monitoring dashboards and observability for production AI systems.

Skills

MLOps

AWS SageMaker

Kubernetes

Python

Docker

Terraform

GitHub Actions

Tools

Docker

Kubernetes

Terraform

GitHub Actions

MLflow

LangChain

LangSmith

Job description

Talenzon group is seeking a Senior MLOps Engineer to join our London-based on-site team for a 6-month contract. You will design and implement an enterprise MLOps platform on AWS, deploy production-ready LLM applications and automate model deployment pipelines.

You will build AI monitoring, governance, and CI/CD workflows, plus standardize the ML lifecycle across teams. Strong English communication and hands-on experience with SageMaker, EKS, and vector databases are required.