Aws Mlops Engineer

Spectrum IT Recruitment
London
2 days ago
Create job alert

Job Description

We are looking for a skilled AWS MLOps Engineer to help deploy, automate, and manage production-grade machine learning solutions within our clients AWS environment. This is a great opportunity for a MLOps Engineer to become a vital part on a new data team.

This is a hybrid role with the expectation to be in the London office 1-2 times per week.

Key Responsibilities

  • Deploy ML models as real-time endpoints using Amazon SageMaker * Build and manage batch inference pipelines * Implement CI/CD workflows for ML using Git-based processes * Containerize applications using Docker * Monitor model performance, data drift, and system health using CloudWatch * Automate data pipelines and feature workflows using Python & SQL * Ensure secure access and governance using AWS IAM and best practices

Core AWS Stack

Amazon SageMaker | Amazon S3 | Amazon Redshift | AWS Lambda | Amazon CloudWatch | AWS IAM

What We're Looking For

Strong hands-on experience with AWS ML infrastructure Experience deploying and monitoring ML models in production Proficiency in Python and SQL Knowledge of Docker and CI/CD pipelines Experience with Infrastructure-as-Code (CloudFormation preferred)

This role focuses on transforming machine learning from experimentation into secure, scalable, production-ready systems.

Spectrum IT Recruitment (South) Limited is acting as an Employment Agency in relation to this vacancy.

Related Jobs

View all jobs

AWS MLOps Engineer

AWS MLOps Engineer

AWS MLOps Engineer

AWS MLOps Engineer

AWS MLOps Engineer

AWS MLOps Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.