Artificial Intelligence Jobs

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.

CrowdStrike · Israel

Security researcher role on CrowdStrike Intelligence's Advanced Research Team, performing vulnerability research and exploit development across a wide range of targets. Day-to-day work includes analyzing vendor patches, identifying exploits in large file collections, reverse engineering, and building automated data collection and analysis tooling, with published research on the blog or at conferences.

CrowdStrike · Spain

Analyzes large-scale security telemetry, threat intelligence feeds and detection data to surface trends, anomalies and emerging threats. Builds dashboards, data pipelines and KPI frameworks using SQL, Python, Logscale and visualization tools, working cross-functionally with product and engineering teams in the Office of Adversary Strategy.

PhysicsX · New York, United States

Builds and automates high-fidelity electromagnetic models across low- and high-frequency applications, from chip and package design to EMI/EMC, using tools like HFSS, Maxwell and CST. Works at the intersection of CAE and data science, generating simulation data to train ML surrogates, collaborating with customers and mentoring junior engineers.

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.

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.

Wayve · London

Owns the autonomy performance measurement framework for a public-scale robotaxi deployment, defining metrics, dashboards and release gates for an end-to-end learned driving system with no existing playbook. Runs the performance improvement loop across model, robot software, backend and evaluation tooling, leading cross-functional execution without direct reporting authority while staying hands-on in Python, C++ and SQL.

Wayve · London

Lead large-scale data enrichment and curation for the Core Model Safety team, mining hard and rare events and building workflows across pre/mid-training, reward modelling and self-supervised labelling. Design and train out-of-distribution detection mechanisms for robust driverless operation, working at the intersection of model engineering, infrastructure, compute and data.

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.

ElevenLabs · United Kingdom

Builds and scales data pipelines from ingestion to delivery, implementing dbt best practices, data standards and quality controls. Develops self-service tooling and documentation so teams like Engineering, RevOps and Growth can access data independently, and creates AI agents to answer data questions. Works remotely within a lean, high-velocity data team.

Hays Technology · United Kingdom · £90,000 – £100,000 pa

Hands-on technical lead for a large-scale AI programme at a digital consultancy, turning architectural direction into production-grade systems across complex legacy and multi-cloud environments. Responsibilities span RAG pipelines, semantic search, embedding infrastructure, orchestration, Responsible AI guardrails, LLMOps and mentoring client-side engineers.

Speechmatics · Cambridge

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

Scale AI · London

Leads a forward-deployed engineering team acting as the technical bridge between AI capabilities and strategic enterprise customers. Involves designing custom integrations, ETL pipelines and production AI agents, plus prompt engineering, RAG systems and evaluation frameworks, deployed within customer security and compliance boundaries.

Thought Machine · Lisbon, Portugal

Full-stack role building end-to-end features across web applications and backend services, with React and TypeScript on the front end and REST APIs behind. Engineers own requirements from design and task breakdown through testing, debugging and production, working in a cross-functional team for banking clients.

Darktrace · Cambridge

Acts as the go-to authority in a chosen reliability specialism—observability, performance engineering, data infrastructure, security-focused SRE or network reliability—defining standards and best practices across SRE, Platform Engineering and DevSecOps. Builds tooling and automation, leads deep-dive investigations into systemic issues, and contributes to incident response and on-call rotations in a cloud-native, Kubernetes-based environment.