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Explore opportunities across consulting, application engineering, cloud, data, cyber security, quality engineering, support and industry technology. Every published role includes the context candidates need to assess fit before applying.

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Careers at RC

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Current openings are organised around specific positions rather than a generic resume collection. Select a role to review its job description, technology environment, industry context, qualifications, experience level, working style and location.

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Current openings

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Select an opening from the role list. The full job description remains in the main panel so candidates can compare positions without navigating through disconnected career pages.

Artificial Intelligence

MLOps Engineer

Engineer repeatable model deployment, evaluation, monitoring and lifecycle controls for machine-learning and AI services.

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LocationLondon, UK
Working styleHybrid / client-aligned
Employment typeFull-time
Experience5–9 years

Technology environment

MLflowAzure MLSageMakerDatabricksDockerKubernetesTerraformCI/CDObservability

Industry context

Banking & FinanceAutomotiveMediaProfessional Services

Job description

The MLOps Engineer will establish production controls around model versioning, deployment, monitoring, rollback and infrastructure automation.

Key responsibilities

  • Build CI/CD pipelines for model and inference-service releases.
  • Implement model registry, versioning and environment promotion controls.
  • Configure monitoring for model quality, drift, latency and infrastructure health.
  • Automate infrastructure and deployment patterns.
  • Support rollback, incident response and lifecycle governance.

Qualifications

  • 5–9 years of DevOps, platform, data or ML engineering experience with production ML exposure.
  • Strong cloud, containers, CI/CD and infrastructure-automation capability.
  • Understanding of model lifecycle, evaluation and operational monitoring.

Preferred qualifications

  • MLflow, Databricks, Azure ML or SageMaker experience.
  • Kubernetes and Terraform expertise.
  • Experience supporting regulated AI workloads.

Benefits & employment terms

  • Compensation, leave, pension and any role-specific benefits are confirmed during the recruitment process and stated in the written offer.
  • Any client-site, travel, security-screening or right-to-work requirements are confirmed before appointment.

Nature of working style

  • Work is organised around defined delivery outcomes, documented responsibilities, peer review and clear escalation paths.
  • Hybrid or client-site attendance varies by engagement and is confirmed before assignment.

Location

London-based with UK client-site collaboration where required.

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Working at RC

Delivery standards shape the employee experience

Technology roles are organised around accountable delivery, professional engineering practices and clear client or project outcomes.

01

Client-impact work

Roles are connected to defined business or delivery outcomes rather than artificial internal assignments.

02

Professional craft

Engineering, consulting and delivery decisions are expected to be explainable, maintainable and grounded in the operating context.

03

Clear ownership

Responsibilities, interfaces, quality expectations and escalation paths should be visible across teams and engagements.

04

Continuous learning

Capability grows through real delivery, peer review, feedback and exposure to changing technologies and business environments.

Hiring journey

A structured process from application to decision

The exact interview sequence may vary by role, but candidates should understand the purpose of each stage and the position they are being assessed for.

01

Apply

Submit your details against a specific published role together with the requested resume and cover letter.

02

Role review

Relevant experience, capability and work context are reviewed against the actual vacancy requirements.

03

Interview / assessment

Where appropriate, discussions explore practical experience, judgement, communication and role-specific capability.

04

Decision

Next steps are communicated in the context of the published vacancy and applicable checks or approvals.

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