Artificial Intelligence Jobs

• London
• Hybrid
• Senior

Customer-facing, billable engineering role building and productionizing data and AI solutions on the Databricks platform. You own architecture and design decisions, delivering end-to-end systems spanning data engineering, ML/AI model integration and user-facing applications, embedding with client teams and travelling to customers around 20% of the time.

Databricks · AWS · Azure +7

• London
• Remote
• Senior · manages people

Lead and scale the UK Forward Deployed AI Engineering team, delivering professional services engagements that help EMEA customers productionise GenAI and ML applications. The role combines people leadership, executive customer relationships, and cross-functional work with Product, Research and Sales to shape delivery models and the product roadmap.

Databricks · AWS · Azure +7

• Romania
• Remote
• Senior · manages people

Lead applied research applying LLMs, deep learning and other modern AI techniques to cybersecurity, architecting research strategy and making decisions on model architectures, training and deployment. Build production AI systems at massive scale while mentoring scientists and aligning technical strategy with senior leadership.

CrowdStrike · LLM · Deep Learning Frameworks +2

• United Kingdom
• Remote
• Lead · manages people

Lead a team of three data scientists at the intersection of machine learning, big data and cybersecurity, setting technical standards and driving strategy for threat detection and agentic AI systems. Work spans research through production deployment, using CrowdStrike's large-scale behavioural and malware data, while mentoring the team and partnering with security research, engineering and product.

AWS · Linux

• London
• Hybrid
• £225,000 – £255,000 pa
• Mid-level

Partner-facing role embedding with nonprofits, research institutes and academic medical centres to apply Claude to clinical development for rare and neglected diseases. You'll design and review trial protocols, build tools for drug repurposing from literature, omics and patient data, and create reusable infrastructure like MCP servers and benchmarks.

Claude · MCP

• Cambridge
• Hybrid · 2–3 days in office
• Mid-level

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.

Docker · Kubernetes · GPU +1

• London
• Hybrid · 2–3 days in office
• Senior

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.

GQA · KV-caching · Flash Attention +2

• London
• Mid-level
• Contract

Builds agentic workflows and internal tools using Anthropic Claude, OpenAI and API ecosystems to automate static and video ad production. Architects MCP servers and context/prompt frameworks connecting LLMs to data sources and asset repositories, while partnering with creative strategists and designers to turn workflow bottlenecks into scalable code.

Anthropic Claude · OpenAI · Model Context Protocol +6

• Zürich, Switzerland
• Senior

Design, develop and optimise GPU/CPU-accelerated data processing libraries such as DALI and nvImageCodec, covering numerical algorithms, performance tuning and benchmarking across architectures. Works closely with leadership and external partners on technical roadmaps, and provides technical leadership and guidance to other library engineers.

CUDA · DALI · nvImageCodec +1

• United Kingdom
• Remote
• Senior

Design, develop and optimise GPU/CPU-accelerated numerical libraries such as DALI and nvImageCodec, with heavy focus on performance tuning, benchmarking and CUDA-based parallel algorithms. The role also involves setting technical roadmaps with partners and providing technical leadership to other library engineers.

CUDA · DALI · nvImageCodec +1

• Cambridge, United States
• Hybrid · 3 days in office
• Senior · manages people

Designs and leads in vitro and cellular pharmacology strategies for small-molecule drug discovery programmes, defining screening cascades and overseeing biophysical, biochemical and cell-based assays. Works closely with AI/ML, medicinal chemistry, structural biology and in vivo teams, and manages external CRO activities to link computational predictions with laboratory validation. Some roles include line management of 2-3 scientists.

SPR · ITC

• Liverpool
• On-site
• £61,165 – £68,817 pa
• Senior
• Permanent

The role involves leading applied AI in marketing research and scholarship, mentoring academic colleagues, and collaborating with subject and programme leaders to shape teaching and research strategy. It supports the business school's AACSB accreditation and TEF Gold aims, requiring a strong publication record and innovative, high-impact teaching.

• London
• Hybrid · 2 days in office
• £76,800 – £115,200 pa
• Senior

Designs, builds and maintains AWS and on-prem infrastructure used by ML engineers, data scientists and product teams, with a strong focus on Kubernetes, Helm, Terraform/OpenTofu and GitOps delivery. Also handles platform service requests, incident diagnosis and reliability improvements, working across engineering teams in a surgical AI centre of excellence.

Kubernetes · Helm · AWS +4

• United Kingdom
• Hybrid · 1 day in office
• £90,000 – £100,000 pa
• Lead
• Permanent

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.

LangChain · LlamaIndex · AWS +4

• Munich - Berlin - London - Paris

Builds and deploys reinforcement learning agents for an autonomous aerial platform, owning the pipeline from large-scale simulation training to real-time deployment on flight-ready hardware. Works on multi-agent RL, partial observability and latency-constrained runtime integration in Python, Rust or C++.

GPU-based Simulators