457 jobs for “software engineer”
PhysicsX London
Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, forecasting, anomaly detection) into customer production environments, building scalable training and inference pipelines with Python, PyTorch, Kubeflow and fastAPI. Leads scoping and architecture, mentors engineers, and travels to customer sites roughly 3-4 weeks per quarter.
PhysicsX Singapore
Lead the deployment of ML models and engineering surrogates—deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, and optimisation—into customer production environments. Own scoping, architecture, and success metrics for data/ML systems built with Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow across cloud and on-prem. Mentor engineers and data scientists while travelling 3-4 weeks per quarter to customer sites worldwide.
Harnham - Data and Analytics Recruitment London £80,000 – £85,000 pa
Design, build and deploy scalable AI and machine learning solutions from concept to production, including Generative AI applications using LLMs and orchestration frameworks. Write production-grade Python, apply MLOps practices such as CI/CD, containerisation and monitoring, and build data pipelines for training, fine-tuning and inference. Work hybrid in London alongside data scientists, engineers and business stakeholders on large-scale datasets.
Maxwell Bond London £150,000 – £175,000 pa
Hands-on role building LLM agent and retrieval systems on a small UK core team, reporting to the Head of Engineering. Work spans LangGraph/LangChain workflows, RAG pipelines with Qdrant and GraphRAG on Neo4j, model integration across Anthropic, OpenAI and Bedrock, plus evaluation harnesses and observability. Token cost, latency and auditability are treated as engineering constraints throughout.
Relation Therapeutics London
Join the Platform Team to design and scale Kubernetes-based hybrid compute clusters across private and public clouds, building core platform services and APIs. You will own CI/CD pipelines, monitoring, backup and disaster recovery, and work closely with Machine Learning and Data Science teams to support their computational needs.
Ricoh London
Builds, configures and operates the platforms and services that take enterprise AI solutions from evaluation into secure, scalable production. Works across DevOps, cloud engineering and MLOps with AI specialists, data scientists and security teams, covering CI/CD, automation, monitoring, secrets management and cost optimisation in cloud and hybrid environments.
eFinancialCareers Rugby £160,000 pa
Hands-on staff-level engineering role building production systems in Go, with React and TypeScript work, on an AI infrastructure team's agentic development experience. You'll shape the agent harness, integrations and workflows connecting agents to real development environments, evolving execution, tool use, context management and streaming while setting technical direction.
Ncounter Reading £120,000 – £140,000 pa
Hands-on engineering leadership role in a technology consultancy serving National Security & Defence, blending people management with technical ownership. You'll lead a multidisciplinary software, platform and DevOps team, define architecture and standards across cloud-native, AI/ML and MLOps platforms, and oversee production delivery into customer environments. Distinct for requiring SC or DV clearance and defence experience while remaining close to the technology.
Anthropic London £325,000 – £485,000 pa
Set the technical direction for agent-driven cluster lifecycle management, provisioning, updating and decommissioning compute clusters across major clouds and own datacenters. Partner with security, research and cloud providers on high-bandwidth connectivity, scalability and fault tolerance, while mentoring engineers and evolving operational-excellence practices.
Anthropic London £225,000 – £255,000 pa
Embed directly with strategic enterprise customers to ship production AI applications built on Claude models, delivering artifacts like MCP servers, sub-agents and agent skills. Combines hands-on Python engineering with customer-facing discovery, codifying repeatable deployment patterns and feeding insights back to Product and Engineering. Founding FDE role with frequent travel (25-50%) to customer sites.
Databricks London
Customer-facing, billable engineering role owning architecture and design decisions while building production-grade data and AI systems on the Databricks platform. Involves embedding with client teams, integrating with their systems, and delivering end-to-end pipelines, ML/AI models and user-facing applications, with around 20% travel to customer sites.
OpenAI London
Partner directly with Digital Native customers to design, build and deploy AI-powered products, taking ideas from early experimentation through evaluation, production launch and scale. Hands-on coding in Python to build prototypes, evaluation harnesses, integrations and production accelerators, while making decisions across models, agents, retrieval, reliability, latency, cost, safety and governance.
Wayve London
Lead the technical architecture and roadmap for onboard localisation, designing and productionising state-estimation systems that fuse GNSS, IMU and wheel odometry for accurate vehicle pose estimates. The role spans algorithm design, prototyping, validation and deployment on real-time vehicle platforms, with hands-on technical leadership and mentorship across robotics, calibration, controls and sensor teams.
Databricks London
Customer-facing engineering role building and productionizing data and AI solutions on the Databricks platform for emerging enterprise and digital native accounts. You own architecture and design decisions, implement end-to-end systems spanning data engineering, ML/AI and application development, and embed with client teams. Billable delivery work with roughly 20% travel.
Speechmatics Cambridge
Work on complex R&D projects within a Modelling Team that trains large self-supervised speech models and deploys them to production. Involves distributed training, transformer architectures, and inference optimisation, with mentoring and cross-department collaboration.
