Machine Learning Jobs

• London
• Hybrid · 3 days in office
• Mid-level

Join the Compute Infrastructure team to keep a planet-scale GPU accelerator fleet healthy and efficient. You'll build observability and telemetry pipelines, automate recovery, hunt compute waste, and optimise accelerator utilisation for large-scale training and inference, working closely with ML infrastructure and research teams.

GCP · Kubernetes · Nvidia GPU +1

• London
• Hybrid · 3 days in office
• Lead

Technically lead the Platform group, designing, operating and refining research, development and production cloud infrastructure across GCP, Kubernetes, Docker and Terraform. The role spans core technical decisions, tooling and CI/CD processes, working closely with scientists, ML researchers and product teams, and reports directly to the Director of Engineering.

GCP · Kubernetes · Docker +7

• United Kingdom
• Remote
• Senior

Serves as the primary technical contact for academic and research partners, driving adoption of NVIDIA's accelerated computing and AI stack. Works hands-on with researchers on large language model training, fine-tuning, inference and agentic workflows at supercomputing scale, delivering workshops and mentoring power users. Involves around 30% travel and close collaboration with research labs and university faculty.

NVIDIA AI Enterprise · NeMo Framework · Megatron Bridge +7

• London
• Hybrid
• Senior
• Permanent

Customer-facing cloud technologist role in AWS's UK Solutions Architecture team, focused on the Travel and Hospitality industry. You lead architecture reviews, whiteboarding sessions, demos and workshops, manage the overall technical relationship with customers, and create reference architectures and technical content across AI/ML, serverless, containers, analytics and security.

AWS

• London
• Hybrid
• Lead
• Permanent

Own end-to-end system architecture for the Wayve AI Driver across L0–L4, defining interface contracts, ECU and sensor requirements, and safety mechanisms. Lead technical alignment with OEMs, Tier 1s and partners, and support integration, bring-up and system-level debugging on vehicles and HiL/ViL benches.

Linux · RTOS · ECU +3

• London
• Hybrid
• Mid-level
• Permanent

Builds full-stack geospatial services in Python and TypeScript, plus PySpark and Databricks pipelines that enrich fleet data with road-network and mapping information at global scale. Owns route-planning applications, map data preparation for training and simulation, and deployment on Azure and Kubernetes end to end.

Databricks · Mapbox · TomTom +10

• London
• Mid-level
• Permanent

You will own the technical relationship with AWS customers in the Travel and Hospitality sector, leading architecture reviews, white-boarding sessions, demos and workshops while advising C-suite and line-of-business stakeholders. The role blends business acumen with deep technical guidance across AI/ML, serverless, containers, analytics and security, and includes creating reference architectures and sharing best practices at scale.

AWS

• United Kingdom
• Hybrid

Designs and builds proactive agentic systems, from sensor-edge reasoning to high-level planning, with stateful multi-turn reasoning, persistent memory and evaluation pipelines. Works across Python, TypeScript, LangGraph, CrewAI, MCP and cloud infrastructure, partnering with biologists and roboticists to take experimental AI from prototype to production.

NextJS · Pydantic · LangGraph +7

• United Kingdom
• Hybrid
• Lead

Senior technical role architecting agentic AI systems for defence and security clients, acting as technical lead on complex projects and setting departmental technical direction. Involves hands-on engineering in Python, client-facing proposal work, mentoring engineers and conducting technical interviews. Requires SC security clearance and UK residency.

• London
• Hybrid · 2–3 days in office

Owns the infrastructure behind speech AI models, building scalable data pipelines for ingesting, transforming and validating large training datasets, plus web scraping and data acquisition tooling. Also operates the platform for training, evaluating and serving models, optimising GPU utilisation, scheduling and observability across distributed systems.

Docker · Kubernetes

• Cambridge
• Hybrid · 2–3 days in office

Own the infrastructure behind speech AI models, building scalable data pipelines for ingesting, transforming and validating large training datasets, plus web scraping and data acquisition. Operate the platform that trains, evaluates and serves models in production, optimising GPU utilisation, scheduling and observability across distributed systems.

Docker · Kubernetes

• Sofia, Bulgaria
• Hybrid
• Senior

Maintains and improves a live customer-facing slot-availability application while writing Terraform/OpenTofu infrastructure as code for cloud environments. Extends backend services, APIs and data pipelines, and modernises the platform by tuning Airflow/Composer and reducing technical debt. Works in a small distributed team with monitoring, alerting and incident response duties.

Python · TypeScript · Terraform +7

• London
• Hybrid
• Lead

Sits within the Insight Enablement function of the Tesco Insights team, shaping longer-term enablement strategy and transformation initiatives so client-facing teams can deliver value. Defines enablement propositions and frameworks across products and tools, connects stakeholder needs with business priorities, and champions adoption of AI and emerging technologies.

• London
• Hybrid · 1–2 days in office
• £75,000 – £85,000 pa
• Senior

Own the ML Ops function within a growing AI and data organisation, building and maintaining production-grade ML orchestration pipelines with Dagster, Airflow or Prefect. Deploy, monitor and scale ML and LLM-powered services on Kubernetes using Terraform or Bicep, with strong CI/CD and observability practices, working closely with data scientists and client-facing teams.

Dagster · Airflow · Prefect +5

• Cambridge
• Mid-level

Hands-on compiler engineering focused on kernel generation and computational graph optimizations for next-generation NVIDIA GPUs, solving complex compilation problems for AI inference and training workloads. Works with MLIR, C/C++ and Python, collaborating with software, hardware and research teams on hardware/software co-design and datacenter-scale AI deployment.

MLIR · GPU · CPU +1