Artificial Intelligence jobs in United Kingdom
24 Feb 2026 1658810 Site Reliability Engineer - Systems Integrator $120000-$150000 City of Sydn[...]
Hamilton Barnes Limited
REABLEMENT & BRIDGING ASSESSMENT OFFICER
Cardiff Council
Lecturer - Foundation Year (Business)
Arden University Ltd
Graduate Development Programme (Feb 2027)
Unitec Institute of Technology
Barista Maestro - Weekend flexibility
Costa
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The Access Group
Barista - Full Time 35 Hours
Costa
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Dubizzle Limited
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Haringey GP Federation
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Transformationunitgm
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Northumbria Police
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Vodafone Group Plc
Barista, FT 30hours ,E6 6LH
Costa
VodafoneThree - Business Insights and Planning Manager
Vodafone Group Plc
Principal Advisory Solution Architect - Moveworks
ServiceNow
Corporate Marketing, Principal Sr
Epicor Software Corp
Site Reliability Engineer - Systems Integrator
Job summary
A fast-growing IT services firm in Chippenham is looking for an expert in AI Ops and MLOps to design and manage AI/ML production pipelines. In this role, you will work with Kubernetes to deploy workloads, optimize model performance, and ensure compliance of AI systems. Ideal candidates will possess strong experience with Python, ML frameworks, and cloud platforms, with a competitive salary ranging from $120,000 to $150,000. Join to leverage your skills in a hybrid work environment.
Benefits
Qualifications
- 3+ years of experience in AI Ops, MLOps, DevOps, or ML infrastructure roles.
- Strong Python skills and experience with ML frameworks.
- Hands-on experience running ML workloads on GPUs.
Responsibilities
- Design, build, and operate AI/ML production pipelines.
- Deploy, scale, and manage inference and training workloads.
- Productionize machine learning models using CI/CD and MLOps best practices.
Skills
Ready to be the guardian of critical business data and systems?
Join a fast-growing Australian IT services firm transforming how companies protect, recover, and leverage their digital assets. From cloud and disaster recovery to cybersecurity, the team delivers smart, tailored solutions that keep clients secure, operational, and future-ready, no cookie-cutter approaches, just real impact.
If you thrive on solving high-stakes challenges and want your work to matter every day, apply now!
- Design, build, and operate AI/ML production pipelines on GPU-enabled infrastructure
- Deploy, scale, and manage inference and training workloads on Kubernetes
- Productionize machine learning models using CI/CD and MLOps best practices
- Manage GPU scheduling, resource allocation, and cost efficiency
- Implement monitoring for model performance, data drift, latency, GPU utilization, and system health
- Automate model lifecycle management and retraining workflows
- Partner with data science teams to transition models from development to production
- Ensure scalability, reliability, security, and compliance of AI systems
- Troubleshoot and resolve production AI/ML and infrastructure incidents
- Contribute to platform architecture and internal tooling decisions
- 3+ years of experience in AI Ops, MLOps, DevOps, or ML infrastructure roles
- Strong Python skills and experience with ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)
- Hands-on experience running ML workloads on GPUs (training and/or inference)
- Strong Kubernetes experience, including deploying and operating production workloads
- Experience with Docker and container-based ML systems
- Experience with cloud platforms (AWS, GCP, or Azure), including GPU instances
- Familiarity with CI/CD pipelines and infrastructure-as-code tools
- Understanding of model monitoring, observability, and data drift
- Strong production mindset and problem-solving skills
- Experience with Kubernetes GPU operators, device plugins, or scheduling strategies
- Experience with ML platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI
- Knowledge of distributed training or large-scale inference systems
- Experience with feature stores and modern data pipelines
- Background in platform engineering or site reliability engineering (SRE)
- Familiarity with security, governance, or compliance requirements for AI systems
- Competitive salary and equity options
- Hybrid work model based in Sydney
- High-impact role with ownership over GPU-backed AI platforms
- Opportunity to build and shape foundational AI infrastructure
- Collaborative, engineering-led culture with room for growth
- $120000-$150000
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.