501 to 525 of 591 Cost Optimisation Jobs in the UK

versioning, CI/CD, deployment, monitoring, and maintenance for models/prompts/agents.Implement robust testing (unit/integration), performance benchmarking (latency/cost), and observability (logging/metrics/tracing) for AI services.Collaborate with cross-functional stakeholders to define requirements, success metrics, and rollout plans; communicate complex … industry and operating in regulated environments (auditability, controls, data handling).Exposure to distributed compute/training concepts (e.g., DDP, sharding) and performance/cost optimization.J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals ...

Deliver proactive technical expertise and drive continuous improvement (Tier A included): posture and coverage advisory, tuning/noise reduction, cost/retention optimisation, automation uplift. Own technical deliverables: automation/playbooks where in scope, custom analytics and workbooks. Drive the operational health-check catalogue as scheduled workstreams … trusted advisor , owning the technical customer relationship Experience balancing reactive support (tickets, troubleshooting) and proactive improvement Capability to deliver continuous improvement initiatives (tuning, optimisation, automation) Experience creating technical deliverables (playbooks, dashboards, analytics, reports) Knowledge of defensive security domains (pentest, IR, EASM, DLP, tabletop exercises) Ability to identify security gaps ...

caught before production. Take end-to-end ownership from discovery and design through build, rollout, and operational excellence. Instrument systems with the observability, cost tracking, and audit trails needed to know when they degrade. Apply FinOps and cost-optimization practices to AI workloads, tracking and managing … token, inference, and infrastructure spend so solutions stay cost effective as they scale. Integrate AI solutions with enterprise data systems, APIs, and MLOps/LLMOps tooling, applying sound system design and distributed-systems judgment. Apply responsible-AI judgment proportionate to the risk of each use case, working with ...

exchange. This team sits within engineering leadership and owns the infrastructure layer that lets Kraken run AI workloads with control, speed, reliability, and cost discipline.The team is responsible for GPU and accelerator infrastructure, cluster operations, scheduling, model serving, observability, capacity planning, and cost-efficient compute … backbone that allows Kraken to train, serve, evaluate, and iterate on AI systems in-house where it matters for privacy, latency, reliability, cost, or product differentiation.You will join a small, senior, high-impact team working directly with AI/ML researchers, platform engineers, security teams, and product teams. ...

exchange. This team sits within engineering leadership and owns the infrastructure layer that lets Kraken run AI workloads with control, speed, reliability, and cost discipline. The team is responsible for GPU and accelerator infrastructure, cluster operations, scheduling, model serving, observability, capacity planning, and cost-efficient compute … backbone that allows Kraken to train, serve, evaluate, and iterate on AI systems in-house where it matters for privacy, latency, reliability, cost, or product differentiation. You will join a small, senior, high-impact team working directly with AI/ML researchers, platform engineers, security teams, and product ...

across at least one hyperscaler cloud — and conversant across several — you bring deep, current knowledge of AI/ML services, accelerators, interconnects, and cost levers, and you continuously scan the horizon to identify promising emerging technologies and judge where and when they belong in a real solution. … elevate the architect community, and are ultimately accountable for ensuring the firm delivers AI/ML infrastructure that meets business SLAs, controls cost, scales to frontier workloads, and creates lasting business value. THE WORK Set the overarching technical vision and strategy for compute infrastructure supporting large-scale ...

architecture (Bronze/Silver/Gold layers) Data quality frameworks Schema evolution andoptimization Perform Databricks performancetuning: Cluster optimization Spark job optimization Query tuning Cost optimization Implement Databricks governanceand security using: Unity Catalog Access controls Data lineage Audit capabilities Lead migration projectsfrom legacy dataplatforms to DatabricksLakehouse. Define best practicesfor … Knowledge of streamingtechnologies: Structured Streaming Kafka Experience with datagovernance, compliance,and enterprise securityframeworks. Key Competencies Strong Databricks architectureand implementation expertise. Ability to designscalableand cost-efficientLakehouse solutions. Strong troubleshooting andperformance optimizationskills. Ability to leadtechnical discussions withenterprise stakeholders. #J-18808-Ljbffr ...

teams and accelerate BAU and delivery programsExperience in Azure Networking (vWAN, Azure Firewall, Express Route) and Azure Policy GovernanceAdept in Azure FinOps/Cost OptimisationIn-depth knowledge around infrastructure automation and orchestration (e.g., Ansible, Terraform, GitLab)Technical … proficiency in Microsoft Technologies, Ubuntu, Red Hat, VMWare VCF, Data Centre, Enterprise networking, WAN/LAN/WLAN, Routing, Firewall, IDS/IPS, WAN optimisation, ZTNA services, Load BalancingStrong understanding of Infrastructure Security, PAM, IAM, and Cloud AuthenticationBenefits:Opportunity to contribute to a significant infrastructure transformation projectHybrid working model ...

tooling (Weights & Biases, LangSmith, MLflow). A product‐first mindset: Fluency with evaluation frameworks (Ragas, DeepEval) and a track record of managing latency, cost, and hallucination tradeoffs in a live product, not a lab setting. Job responsibilities What You’ll Do Own end‐to‐end delivery: Architect … ship AI products, agentic frameworks, and multi‐modal application backends into production. Set the evaluation bar: Establish continuous evaluation pipelines, guardrails, observability, and cost‐optimization strategy for production LLM deployments. Decide the stack: Own build‐vs‐buy calls e.g. self‐hosted vLLM vs. a managed endpoint ...

tooling (Weights & Biases, LangSmith, MLflow). A product-first mindset: Fluency with evaluation frameworks (Ragas, DeepEval) and a track record of managing latency, cost, and hallucination tradeoffs in a live product, not a lab setting. Job responsibilities What You’ll Do Own end-to-end delivery: Architect … ship AI products, agentic frameworks, and multi‐modal application backends into production. Set the evaluation bar: Establish continuous evaluation pipelines, guardrails, observability, and cost‐optimization strategy for production LLM deployments. Decide the stack: Own build‐vs‐buy calls e.g. self‐hosted vLLM vs. a managed endpoint ...

tone, lexicon, and domain-specific tasks that are currently brittle in promptsInvestigates inference efficiency and tokenomics: cost-per-output, model routing, and optimisation of production inferencePrototypes voice and image/multimodal capabilities (speech-to-text, text-to-speech, voice agents, document and image understanding) to underwrite future … evaluation, and benchmarking of ML systemsAbility to bridge research and engineering: prototypes that become production-ready capabilitiesAwareness of inference cost, performance, and optimisation techniquesStrong communication skills, including translating research into business and engineering termsPublished in a top-tier AIML venue (e.g. NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR ...

primitives.Set technical direction for the future of the company's centralised GenAI platform — including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimisation, and other post-training and agentic techniques — enabling the next generation of AI-powered products, agents, automation, and personalisation.We’re excited about you because...BSc … training pipelines (SFT, DPO/RLHF, LoRA), including data preparation and evaluationGPU performance work — multi-node/distributed inference, KV-cache/memory optimisation, quantisation (FP8/INT8/AWQ/GPTQ), or cold-start/throughput tuningExperience with Kubernetes, cloud infrastructure (AWS/GCP), GPUs, serverless/elastic ...

technical direction for the future of the company's centralised GenAI platform - including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimisation, and other post-training and agentic techniques - enabling the next generation of AI-powered products, agents, automation, and personalisation. We're excited about you because... … training pipelines (SFT, DPO/RLHF, LoRA), including data preparation and evaluation GPU performance work - multi-node/distributed inference, KV-cache/memory optimisation, quantisation (FP8/INT8/AWQ/GPTQ), or cold-start/throughput tuning Experience with Kubernetes, cloud infrastructure (AWS/GCP), GPUs, serverless ...

workflows and processes, improve efficiency and drive business outcomes.Bonus Points:Building & scaling distributed systems on large-scale bare metal & virtual data center infrastructure.A cost optimization and cost-of-goods-sold focus.Professional Go programming language experience writing scripts/applications for automation, tools, dashboards, and/ ...

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). We also own core platform surfaces … including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution.About the RoleYou will join a small, high-leverage team building production infrastructure for Generative AI at Deliveroo and DoorDash, with a primary focus on our open-weights model platform spanning inference and fine-tuning: real-time ...

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). We also own core platform surfaces … including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the RoleYou will join a small, high-leverage team building production infrastructure for Generative AI at Deliveroo and DoorDash, with a primary focus on our open-weights model platform spanning inference and fine-tuning: real ...

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). We also own core platform surfaces … including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at the company and DoorDash, with a primary focus on our open-weights model platform spanning inference and fine ...

caught before production. Take end-to-end ownership from discovery and design through build, rollout, and operational excellence. Instrument systems with the observability, cost tracking, and audit trails needed to know when they degrade. Apply FinOps and cost-optimization practices to AI workloads, tracking and managing … token, inference, and infrastructure spend so solutions stay cost effective as they scale. Integrate AI solutions with enterprise data systems, APIs, and MLOps/LLMOps tooling, applying sound system design and distributed-systems judgment. Apply responsible-AI judgment proportionate to the risk of each use case, working with ...

continuous improvement across system performance, reliability, observability and operational excellence. Promote architecture decisions that balance customer experience, technical quality, speed of delivery and cost efficiency. Leadership & Collaboration Lead, coach and develop a multidisciplinary architecture and technical quality team, creating a culture of collaboration, innovation and continuous improvement. Build … platform reliability approaches, with exposure to tools such as Datadog being advantageous. Experience balancing technical excellence with commercial considerations, including scalability, performance and cost optimisation. Strong stakeholder management skills, with the ability to influence technical and non‐technical audiences. Experience leading and developing high‐performing architecture or technical ...

business workflows into orchestrated, governed multi-agent systems built on the Microsoft AI stack. Your designs will prioritize human-in-the-loop controls, cost efficiency, and enterprise-grade scalability right from the start.Key Responsibilities:• Agentic Architecture: Design advanced agentic workflow architectures, including agent orchestration, tool utilization, memory/… loop workflows, ensuring approval, escalation, and exception-handling patterns strike the perfect balance between high automation rates and commercial risk management.• Cost Management: Own AI cost optimization across the agent estate by managing model selection and routing, context retention, caching, and token budgeting.• Enterprise Deployment: Plan ...

infrastructure (vector stores, eval platforms, AI gateways, model routers, agent frameworks), and own the technical rationale behind themDrive cost, latency and throughput optimisation across our production GenAI systems, with the trade-offs documented and explicitDefine our principles for emerging paradigms, including multi-agent protocols, multimodal systems … code: Python and modern API-driven architectures on cloud infrastructure (AWS or equivalent), with the production engineering instincts (CI/CD, observability, SLOs, cost attribution) to take prototypes through to hardened productionCurrent, hands-on expertise across the GenAI stack: LLM APIs, prompt engineering, RAG (hybrid retrieval, chunking strategy ...

standards and expectations.Our projects are diverse, and your focus could include value creation, commercial and operational excellence, revenue growth, cost and margin optimisation and operating model design.Our culture is highly collaborative and team-oriented, and our people enjoy a hybrid work model, balancing client proximity, the convenience … delivering transformation engagements for clients across various tech intensive industries.experience in value creation, commercial or operational excellence, revenue growth, cost and margin optimisation and operating model design, programme recovery and turnaround.Additional InformationOn top of this role being an exciting career opportunity, we offer many attractive benefits, including ...

maintain RBAC/OIDC access controls and disciplined API key lifecycle management across the platform. Build caching layers and cost/latency optimisation strategies, and the adoption and reuse analytics that show whether the platform is actually being used. Contribute to API design, versioning, and promotion workflows ...

maintain RBAC/OIDC access controls and disciplined API key lifecycle management across the platform. Build caching layers and cost/latency optimisation strategies, and the adoption and reuse analytics that show whether the platform is actually being used. Contribute to API design, versioning, and promotion workflows ...

maintain RBAC/OIDC access controls and disciplined API key lifecycle management across the platform. Build caching layers and cost/latency optimisation strategies, and the adoption and reuse analytics that show whether the platform is actually being used. Contribute to API design, versioning, and promotion workflows ...