MLOps Engineer

2 weeks ago

London, Greater London, United Kingdom FitNext Co. Full time £45,000 - £90,000 per year
On-Site MLOps Engineer (Kubernetes, Cloud, ML Workflows)

London, UK – Soho (next to Tottenham Court Road) | Contractor | Start: ASAP

About the Role

Strong MLOps engineer with exposure in high-volume systems to help implement best practices and scale MLOps practice for a global brand. Must have strong on-prem and Kubernetes experience. This role includes an on-call rotation. You'll collaborate with ML engineers and product teams, bringing infrastructure excellence and MLOps innovation to a rapidly scaling environment.

This is a hybrid role with 3 days on-site in London (Soho, near Tottenham Court Road). Applications are considered only from candidates able to work on-site.

Required Skills

  • Strong on-prem as well as AWS cloud experience

  • Expertise managing GPU-enabled Kubernetes clusters for scalable and distributed systems

  • Deep understanding of the ML lifecycle in production, including deployment, versioning, and monitoring

  • Proficiency in Python or Go (3+ years experience required), focused on building automation and tooling for ML

  • Experience with CI/CD tools like ArgoCD or GitHub Actions for ML workflows

  • Skilled in using observability tools such as Prometheus, Grafana, and cloud-native stacks

  • Hands-on experience with Docker and container orchestration in cloud-native or hybrid environments

  • Familiarity with Infrastructure-as-Code tools, especially Terraform

  • Capable in cloud environments (AWS, GCP, or Azure) with exposure to AI/ML services

  • Confident in incident response, with experience participating in on-call rotations

Bonus Skills

  • Experience with AWS ML services like SageMaker and Bedrock

  • Enthusiasm for exploring emerging MLOps tools and practices

  • Demonstrated ability to support data scientists by building scalable ML experimentation infrastructure

Experience & Requirements

  • 7+ years of DevOps experience with high-scale, distributed systems

  • 2+ years of hands-on experience in MLOps environments

  • Experience managing on-prem systems and Kubernetes clusters

  • 3+ years of Python or Go experience

  • Familiarity with CI/CD tools for ML workflows and Infrastructure-as-Code

Hiring Process

  • 1 technical interview with BarRaiser

  • 2 technical rounds

  • 1 final HR round

Other Details

  • Rate: Up to $65/hr

  • Long-term contractor engagement (commission paid over 10 months)

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