Artificial Intelligence Jobs

Entrust · Lisbon, Portugal

Builds and operates production ML systems for document classification and extraction, using VLM/LLMs and traditional ML to power identity verification for millions of users. Leads technical design from RFC to deployment, optimises GPU inference, and designs training, evaluation and labelling pipelines. Works in a squad-based team alongside Applied Science, Product and Data Science, mentoring engineers and driving reliability and scalability.

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.

Anthropic · London · £225,000 – £255,000 pa

Serve as a trusted technical advisor to high-growth startups building on the Claude Developer Platform, leading deep engagements that include pair programming, architecture reviews, and code contributions. Develop evaluation frameworks, prototypes, and technical documentation, and feed patterns back to Product and Engineering. Requires production LLM application experience and frequent travel to customer sites.

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 owning architecture and design decisions while building production-grade data, AI and application systems on the Databricks platform. You embed with client teams, from technical ICs to executives, to scope and deliver end-to-end solutions, contributing reusable accelerators and product feedback. Requires hands-on coding in Python, Scala or TypeScript, deep Apache Spark and distributed computing expertise, and multi-cloud knowledge, with around 20% travel to customer sites.

Reperio Human Capital · Dublin, Ireland · £388 – £474 pd

Hands-on engineering role owning AI/ML initiatives end-to-end, from solution design and experimentation through deployment, monitoring and optimisation. Involves building production ML and GenAI solutions including RAG architectures, working with Snowflake and cloud data platforms, and developing Python and R software with strong MLOps, CI/CD and DevSecOps practices. Collaborates with data, product and business teams to turn ambiguous problems into scalable, secure solutions.

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.

Speechmatics · London

Join the Modelling Team to train large self-supervised and transformer-based speech models, deploying them into production with strong software engineering and model-serving practices. Work on complex R&D projects, optimise inference, and mentor engineers in a hybrid London setup.

Searchability · Manchester · £90,000 – £100,000 pa

Designs, builds and optimises production-grade AI solutions focused on RAG, LLMs and agentic workflows. Works with AI Platform Engineers to develop RAG pipelines, improve retrieval, implement fine-tuning and establish evaluation frameworks, while contributing to technical decisions, code reviews and mentoring.

WeDoTech · London · £800 – £1,000 pd

Senior hands-on staff engineer driving adoption of Agentic AI and production ML across multiple engineering teams. Defines reusable architectures and patterns, builds production RAG and LangGraph/LangChain systems, and improves AI evaluation, observability, MLOps and model-risk controls in a regulated environment.

Wayve · London

Sets technical strategy and roadmap for fault detection and fallback systems in an autonomous driving stack, designing and training detection mechanisms for robust driverless operation. Leads integration into the shared driving stack, aligning ML, inference optimisation and software teams, and mentors through architecture reviews. Works with large-scale training and fleet data in a small, high-impact team.

DCV Technologies · London

Designs and builds agentic AI systems with multi-step reasoning, planning and action execution, using Python, Azure OpenAI, Semantic Kernel and LangGraph for multi-agent orchestration. Works on RAG architecture, vector stores, MCP tool integration and productionising LLM services for a major UK retailer, with a focus on performance, cost, latency, governance and responsible AI.

Medtronic · Edinburgh · £76,800 – £115,200 pa

Designs and manages complex research data pipelines spanning clinical study data collection through validation trials, supporting an AI and algorithm R&D team. Owns data architecture, storage, security and ETL/ELT workflows across sensor platforms and HPC environments, working with Python, SQL and CI/CD automation to enable machine learning and signal processing applications.

University of Bristol · Bristol · £44,746 – £50,253 pa

Builds and operates the software-defined compute and storage/networking platforms behind the UK's most powerful supercomputer, using Python, Rust, Terraform/OpenTofu, Kubernetes, Git and Bash. Works closely with AI researchers to co-design and debug massive-scale GPU and CPU/GPU workloads, with a focus on stability, security and scaling.