Technology - ML Ops Engineer
Leeds, England, United Kingdom
R
GBP 60K-75K (estimate) Mid-level Full Time
Tasks
- Automate deployment and rollback
- Collaborate on safety practices including PII protection
- Define SLOs and SLIs
- Design and operate CI/CD pipelines
- Ensure structured governance traceability and reproducibility
- Implement observability for service data model and cost
- Implement production configuration for LLM deployments
- Implement safe deployment strategies
- Implement secure access controls and secrets handling
- Improve resilience reduce MTTR through automation
- Instrument LLM services for token usage latency and safety
- Lead incident response and post-incident reviews
- Maintain operational runbooks
- Manage prompts and workflows as code with versioning
- Monitor availability latency errors and resource usage
- Monitor data quality freshness volume completeness schema drift
- Monitor model performance and drift
- Operate production machine learning services
- Own end to end MLOps lifecycle
- Package and deploy containerized inference services
- Register and promote models across environments
Perks/Benefits
- Annual leave
- Buy and sell holiday
- CPD support
- Core hours flexible schedule
- Cycle to work scheme
- DBS Check
- Discounted gym memberships
- Employee assistance programme
- Employee discount platform
- Employee discounts
- Enhanced maternity pay
- Enhanced paternity pay
- Green Car Scheme
- Health and beauty discounts
- Hybrid working
- Long service awards
- Mental health support
- Occupational sick pay
- Pension
- Private healthcare insurance
- Professional registration fees covered
- Refer a friend bonuses
Skills/Tech-stack
AKS | Access Control | Alerting | Auditability | Azure | Azure Machine Learning | Azure Monitor | Blue-Green Deployment | Blue/green | CI/CD | Canary Deployment | Circuit Breakers | Container Registry | Continuous Deployment | Data Contracts | Data Drift | Data Quality | Docker | Experiment tracking | Fallbacks | Feature Engineering | Identity Management | Incident Management | Infrastructure as Code | Injection testing | Kubernetes | LLMOps | Log Analytics | MLOps | Machine Learning | Monitoring | Observability | PII protection | Prompt Injection Testing | Prompt engineering | Prompt injection | PyTorch | Python | Reliability Engineering | Retries | SLI | SLO | SRE | Schema drift | Scikit-learn | Secrets management | TensorFlow | Terraform | Token Usage Monitoring | Token usage | Tokenization | Training-serving skew | Usage monitoring | “as-code”
Education
N/A
Roles
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