IT Network Assurance Engineer with TfL, assuring and optimising network infrastructure and managing critical incidents for seamless service delivery.
About the role
- Senior ML Infrastructure Engineer at Gridware responsible for ML infrastructure and deployment processes. Collaborating with core teams to enhance model monitoring and operational efficiency.
Responsibilities
- Design, build, and maintain the infrastructure, tooling, and workflows that enable reliable, scalable deployment of ML models to production.
- Develop monitoring and observability systems to track model performance, data drift, data quality, and overall system health.
- Create and maintain end-to-end testing frameworks and simulation environments to validate models and pipelines prior to deployment.
- Work closely with Data Engineering and Platform Engineering teams to ensure ML systems integrate cleanly with broader Gridware infrastructure and operational standards.
- Improve CI/CD pipelines for ML workloads, ensuring reproducibility, safe rollout, and automated rollback strategies.
Requirements
- 5+ years of experience building production ML infrastructure
- Strong software engineering skills and proficiency in Python
- Experience with cloud platforms (AWS) and container orchestration (Kubernetes)
- Familiarity with feature stores, model registries, or centralized metadata systems (i.e. MLFlow)
Benefits
- Health, Dental & Vision (Gold and Platinum with some providers plans fully covered)
- Paid parental leave
- Alternating day off (every other Monday)
- “Off the Grid”, a two week per year paid break for all employees.
- Commuter allowance
- Company-paid training
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