51 to 72 of 72 Auto-Scaling Jobs in England

systematically improve tail latency (P95/P99) and platform reliability through metrics‐driven engineering. Proven experience owning system‐wide SLIs/SLOs, capacity planning, autoscaling strategies, and mentoring senior and mid‐level engineers. Preferred Direct open‐source or production contributions to modern inference frameworks (e.g., vLLM, Triton, TensorRT ...

interfaces with React, focusing on accessible design, reusable components, and efficient state management. Design and maintain Kubernetes deployments on AKS, including manifests, ingress configuration, autoscaling, configuration and secrets management, service‐to‐service communication, and rollout/rollback patterns. Implement and maintain DevSecOps practices using Azure DevOps, building CI/… experience running workloads on Azure Kubernetes Service (AKS), with solid understanding of Kubernetes fundamentals such as deployments, services, ingress, configmaps, secrets, and horizontal pod autoscaling (HPA). Practical experience with containerisation using Docker and packaging and deployment of containerised workloads. experience designing and executing release strategies, including blue/green ...

DevOps Engineer (Mid-Level) Location: Barcelona, Spain (Hybrid) Language Requirements: English (Required), Spanish (Preferred) About the Role We are looking for a talented Mid-Level DevOps Engineer to join a growing engineering team responsible for ...

checks, and domain registration. System Scaling & Optimization: (Level: Practitioner): Design and implement scalable systems on AWS EC2 and S3, including load balancing, auto-scaling, and performance tuning. Security & Compliance: (Level: Practitioner): Ensure all AWS deployments comply with industrystandard security protocols and company policies. Implement and manage security ...

similar frameworks. Proven ability to optimize microservices for low-latency, high-throughput processing at significant scale. Preferred Qualifications: Familiarity with AWS cloud infrastructure, auto-scaling, blue-green deployments, and building/maintaining SLAs, SLOs, and SLIs. Strong commitment to test-driven development, proactive monitoring, and operational excellence ...

similar frameworks. Proven ability to optimize microservices for low-latency, high-throughput processing at significant scale. Preferred Qualifications: Familiarity with AWS cloud infrastructure, auto-scaling, blue-green deployments, and building/maintaining SLAs, SLOs, and SLIs. Strong commitment to test-driven development, proactive monitoring, and operational excellence ...

quantization, mixed-precision serving.* Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis.* Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads.### **Qualifications:*** 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.* Familiarity with at least one deep ...

/Vertex endpoints, as well as working with feature and model registries, CI/CD, model monitoring, and drift detection. Experienced with cost-efficient autoscaling, GPU scheduling, canary and shadow deployments, and A/B testing. Mandatory Skills: Cloud Engineering GCP.Reinvent your world. We are building a modern Wipro. ...

ingestion and preprocessing through distributed training and evaluation. Build and optimize inference services that deliver low‐latency, high‐reliability experiences for our customers, including autoscaling, routing, and fallbacks. Work on GPU‐level performance : tuning kernels, improving utilization, and identifying bottlenecks across our training and inference stack. Collaborate closely with ...

ramp on the JVM, since much of our current stack is Java. Experience transitioning large single-tenant legacy systems into modern shared-resource, auto-scaling architectures. At Apple, we're not all the same. And that's our greatest strength. We draw on the differences ...

under load. Ensure implementations support horizontal and vertical scaling, efficient resource utilisation, and predictable behaviour as demand grows. Guide and review approaches to autoscaling, and workload management, aligned with agreed architectures. Review cloud implementations to confirm they meet expectations for availability, scalability, cost‐efficiency, and compliance. Operational Excellence & Risk ...

under load. Ensure implementations support horizontal and vertical scaling, efficient resource utilisation, and predictable behaviour as demand grows. Guide and review approaches to autoscaling, and workload management, aligned with agreed architectures. Review cloud implementations to confirm they meet expectations for availability, scalability, cost-efficiency, and compliance. Operational Excellence & Risk ...

maintain high-performance, high-IOPS cloud storage solutions, ensuring seamless data synchronisation, backup strategies, and optimal throughput. Automate the deployment, configuration, and auto-scaling of workload orchestrators, container platforms, and core service components to ensure high resource utilisation and cost efficiency. Enforce strict security protocols across all environments … workloads on AWS using AWS ParallelCluster, SOCA or custom Slurm fleets. Ability to architect for maximum cost efficiency, implementing automated spot-instance utilization, auto-scaling strategies, and Savings Plans optimization. Proficiency in monitoring infrastructure health and application performance using tools like Prometheus, Grafana, ELK stack, or CloudWatch, with ...

thrive. What you’ll do... Compose, build, and operate production‐grade Kubernetes clusters for high‐volume model inference and scheduled training jobs. Configure autoscaling, resource quotas, GPU/CPU node pools, service mesh, Helm charts, and custom operators to meet reliability and efficiency targets. Implement GitOps workflows for environment configuration … orchestration and multi‐agent patterns. Ray, Kubeflow, or similar frameworks. Experience embedding controls, audit evidence, and governance in regulated environments. Experience with GPU efficiency, autoscaling strategies, and workload right‐sizing. About working for us... Our focus is to ensure we're inclusive every day, building an organisation that reflects modern ...

real-world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure … accelerator platforms (GPUs, TPUs, or emerging hardware) Representative projects Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production-grade deployment pipelines for releasing new models to millions ...

weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). … throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ...

harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. Take basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost tuning. Participate in on‐call for your area and drive root‐cause analysis with crisp follow‐ups. 15% Collaborate Pair … evals; hands‐on with time‐series analysis (forecasting, change‐point, drift). Cloud & ops: Basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost control. Communication: You explain results clearly, align stakeholders, and write crisp docs. Bonus points DevOps wizardry; GPU/ ...

resource isolation. Additionally, you will implement advanced optimizations—including micro-batch schedulers, speculative decoding, and KV-cache reuse—while refining capacity planning, autoscaling policies, and mentoring engineers across the team. Who You Are Bachelor’s or Master’s degree in Computer Science or a related technical field (or equivalent practical … improving tail latency (P95/P99) and service reliability through metrics-driven engineering work. Experience defining and owning SLIs/SLOs, managing capacity planning, autoscaling policies, and driving post-incident remediation. Preferred Experience with low-level systems and high-performance computing components (e.g., C++ development, CUDA kernels, NCCL/SHARP ...

# DevOps EngineerMid LevelLondonPosted 7 days ago### Role OverviewWe're actively seeking a highly skilled DevOps Engineer to revolutionize our operational capabilities. Your core responsibilities will center on designing unshakeable automation processes, managing massive cloud ...

offering. ResponsibilitiesDefine Fuse's inference serving strategy and architecture from first principlesDesign and build the serving stack: request routing, batching, scheduling and autoscaling for high-throughput, latency-sensitive inference workloadsOwn model-level optimisation strategy for serving, deciding where and how to apply quantisation, distillation, speculative decoding and similar techniques … playbook: this is a founding role shaping a new function, not joining an established oneBonus: Triton or custom ML inference/training frameworks; autoscaling or capacity planning for large-scale inference; multi-tenant serving or SLA-driven infrastructure; background at a hyperscaler, frontier AI lab or large-scale distributed inference ...

offering. Responsibilities Define Fuse's inference serving strategy and architecture from first principles Design and build the serving stack: request routing, batching, scheduling and autoscaling for high-throughput, latency-sensitive inference workloads Own model-level optimisation strategy for serving, deciding where and how to apply quantisation, distillation, speculative decoding … playbook: this is a founding role shaping a new function, not joining an established one Bonus: Triton or custom ML inference/training frameworks; autoscaling or capacity planning for large-scale inference; multi-tenant serving or SLA-driven infrastructure; background at a hyperscaler, frontier AI lab or large-scale distributed ...

role. Responsibilities Define Fuse's inference serving strategy and architecture from first principles. Design and build the serving stack: request routing, batching, scheduling, and autoscaling for high-throughput, latency-sensitive inference workloads. Own model-level optimisation strategy for serving - deciding where and how to apply quantisation, distillation, speculative decoding … still early-stage, not joining an established one. Nice to Have Experience with Triton or custom ML inference/training frameworks. Experience with autoscaling or capacity planning for large-scale inference workloads. Exposure to multi-tenant serving or SLA-driven infrastructure. Background at a hyperscaler, frontier AI lab, or large ...