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Platform Engineer AWS AI ML

Client Server
Posted 2 days ago, valid for 5 days
Location

London, Greater London N1, England

Salary

£95,000 per annum

Contract type

Full Time

Retirement Plan
In order to submit this application, a TotalJobs account will be created for you. As such, in addition to applying for this job, you will be signed up to all TotalJobs’ services as part of the process. By submitting this application, you agree to TotalJobs’ Terms and Conditions and acknowledge that your personal data will be transferred to TotalJobs and processed by them in accordance with their Privacy Policy.

Sonic Summary

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  • The job is for a Platform Engineer focusing on AWS AI Machine Learning, offering a salary of up to £95k.
  • The position is based in London with a hybrid work-from-home model, requiring attendance in the office 2-3 days a week.
  • Candidates should have experience in a similar Platform, DevOps, or SRE role, with a strong focus on cloud infrastructure and automation.
  • Key skills include knowledge of AWS, IaC tools like Terraform, containerization with Docker and Kubernetes, and familiarity with CI/CD concepts and Machine Learning frameworks.
  • The role offers equity options, 26 days of holiday, private healthcare, a pension plan, and other perks.

Platform Engineer (AWS AI Machine Learning) London / WFH to £95k

Are you a technologist Platform Engineer with an interest in AI and Machine Learning?

You could be progressing your career at a well funded, early stage tech start-up that is using Computer Vision, AI and Machine Learning to create a unique product for major retailers to be able to see how their products are displayed in store and how customers interact with them.

The company is already experiencing success and needs to scale. As the first Platform Engineer hire you will be instrumental in setting up and establishing DevOps and SRE processes and systems and consolidating cloud based services to AWS to support data intensive applications and Machine Learning workflows.

You'll implement and maintain CI/CD pipelines for automated build, test and deployment processes to ensure fast and efficient delivery of software updates and model deployments. And develop and maintain monitoring, logging and alerting systems to proactively identify and address performance issues and security vulnerabilities.

You'll collaborate with cross functional teams to optimise system performance, troubleshoot issues and ensure high availability, in an impactful role which you can shape.

Location / WFH:

You'll join the team in London 2-3 days a week in a hybrid work from home model.

About you:

  • You have experience in a similar Platform / DevOps / SRE role with a focus on cloud infrastructure and automation
  • You have a strong knowledge of cloud technologies (AWS preferred), experience with IaC tools (Terraform, CloudFormation) and Containerisation (Docker, Kubernetes)
  • You have a strong knowledge of CI/CD concepts and experience with tools (Github Actions)
  • You have an interest and knowledge with Machine Learning concepts and frameworks (e.g. PyTorch, TensorFlow)
  • You have strong analysis and problem solving skills

What's in it for you:

  • Salary to £95k
  • Hybrid work from home with flexible working hours
  • Equity options
  • 26 days holiday
  • Private Healthcare including mental health, dental, optical
  • Pension plan
  • Plus other perks such as Cyle to Work scheme

Apply now to find out more about this Platform Engineer (AWS AI Machine Learning) opportunity.

At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.

Apply now in a few quick clicks

In order to submit this application, a TotalJobs account will be created for you. As such, in addition to applying for this job, you will be signed up to all TotalJobs’ services as part of the process. By submitting this application, you agree to TotalJobs’ Terms and Conditions and acknowledge that your personal data will be transferred to TotalJobs and processed by them in accordance with their Privacy Policy.