Find & Apply For Computer Systems Engineer / Architect Jobs in London, Kentucky

Senior MLOps Engineer United States -

London Posted:

05/08/2025

Salary:

£0.00 to £700.00 per

Day ID:

36373_BH Save Share Apply Apply Login OR Register and apply Senior DevOps / MLOps Engineer Outside IR35 | Fully Remote A leading global technology business is seeking a Senior MLOps Engineer to support the evolution and scalability of its machine learning infrastructure. This role offers the opportunity to work on a high-traffic platform with millions of daily data points, enabling meaningful real-world impact through advanced ML systems across areas like content recommendation, safety, and user engagement. The ideal candidate will bring deep experience in managing scalable Kubernetes environments, cloud-native infrastructure, and MLOps tooling, enabling rapid iteration and high-throughput model deployment. Key Responsibilities

• Scale and optimise an internal MLOps platform used across multiple MLfocused teams
• Drive automation, testing reliability, and performance improvements across ML pipelines
• Manage and fine-tune GPU-accelerated Kubernetes clusters to support highavailability, cloud-native workloads
• Support production readiness and system reliability through on-call participation and proactive monitoring
• Evaluate and implement modern MLOps tooling in alignment with the company's cloud and ML strategy
• Collaborate closely with machine learning engineers and product stakeholders to ensure infrastructure meets evolving project demands
• Share knowledge across teams to elevate engineering standards in DevOps, MLOps, and infrastructure reliability Desired Experience
• Strong experience managing GPU-enabled Kubernetes clusters at scale
• Deep understanding of the full ML lifecycle: experimentation, training, deployment, versioning, and monitoring
• Proficiency in languages like Python, Go, or similar, with an emphasis on automation and ML tooling
• Proven track record building infrastructure that accelerates experimentation and model deployment in cloud environments
• Familiarity with CI/CD tools such as ArgoCD, GitHub Actions, or similar, especially for ML use cases
• Experience with observability tools such as Prometheus, Grafana, and cloudnative monitoring solutions
• Comfortable contributing to incident response and participating in an on-call rotation
• Solid experience with containerisation technologies like Docker in hybrid or fully cloud-native environments
• Working knowledge of Terraform and Infrastructure-as-Code principles
• Keen interest in emerging MLOps technologies and cloud-native best practices
• Self-motivated, inquisitive, and passionate about continuous learning
• Experience with AWS or similar cloud platforms is highly desirable, especially in the ML domain Save Share Apply Apply Login OR Register and apply