Artificial Intelligence Jobs

• Singapore
• Lead

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.

Python · PyTorch · Pandas +3

• Singapore
• Senior

Customer-facing engineering role building and deploying applications that put physics AI models into production for industrial clients. You will work directly with customers, data scientists and ML engineers, prototyping tools, iterating on user feedback, and building Python FastAPI microservices deployed on Kubernetes, Terraform and AWS/Azure.

Python · FastAPI · Helm +4

• Romania
• Remote
• Senior
• Permanent

Owns major components of the Windows kernel-mode endpoint sensor, architecting and building anti-virus and EDR features that cut across file system, memory, process and networking subsystems. Works on cross-platform deliverables with shared components across Windows, Mac and Linux, leading projects from design through unit and component testing while mentoring a distributed team.

Windows · Mac · Linux +4

• USA, NY
• Remote
• US$140,000 – US$215,000 pa
• Lead · manages people

Lead a growing team of engineers building self-service infrastructure-as-code primitives, high-availability core services and multi-cloud platforms at massive scale. The role blends people management with hands-on architecture, cloud cost optimisation and SRE practices across AWS and GCP, with hybrid working expected near office locations.

Chef · Puppet · Salt +7

• London
• Hybrid
• Mid-level
• Permanent

Deliver bespoke, production-grade machine learning systems for government and national security clients, spanning the full ML lifecycle from architecture to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, while advising stakeholders and setting deployment standards.

Scikit-learn · TensorFlow · PyTorch +5

• London
• Hybrid
• Mid-level
• Permanent

Builds and deploys production-grade machine learning systems for national security and AI safety clients, including LLM applications, multi-agent tooling and evaluation of frontier models. Involves technical scoping, architectural decisions, and advising stakeholders, with reusable infrastructure work alongside engineers and data scientists.

AWS · Azure · GCP +5

• London
• Senior

Forward-deployed full-stack engineer who partners directly with public sector clients to turn ambiguous mission requirements into production-grade AI applications. Leads architecture across React, Node.js, Python, Kubernetes and global cloud infrastructure, mentoring staff and shaping reusable platform patterns. Founding-member role on Scale's Global Public Sector team.

Python · Node.js · React +4

• London
• Hybrid
• Senior

Owns the software engineering that brings data science and machine learning products into live production for the Autoplanner team, building AI-powered planning systems across global warehouses and last-mile assets. Writes typed, well-tested Python (with some Java for OSP integration), builds APIs and data contracts, manages AWS deployments and CI/CD, and packages, serves and monitors ML models. Acts as engineering partner to data scientists and shares on-call support.

AWS · GCP · Ocado Smart Platform

• United Kingdom
• Remote
• Mid-level
• Permanent

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.

dbt · Python · SQL +2

• London
• Hybrid
• Permanent

Architect novel generative models to design functional proteins, working in an interdisciplinary team of ML researchers, protein engineers and biologists. The role spans data curation, evaluation metrics, rapid prototyping, cloud training/inference optimisation and planning wet lab testing campaigns, with about 10% of time for self-development.

• London
• Lead

Hands-on principal engineer joining a small senior team tackling the hardest technical problems in public sector AI engagements. Shapes technical approach with clients, builds rapid prototypes spanning AI agents, RAG and evaluation pipelines, defines reusable architecture, and mentors engineers across a young organisation.

AWS · GCP · Azure

• London
• Hybrid
• Senior
• Permanent

Builds and operates the platform running long-lived agentic workflows, where a single run can last hours and fan out across dozens of subagents. Work spans durable execution, checkpointing and retries, LLM integration with guardrails, and tracing and cost attribution across services and two languages, weighted towards backend and platform in TypeScript and Node.js.

Restate · PostgreSQL · Google Cloud +7

• London
• Hybrid
• Senior
• Permanent

Builds and operates the platform running long-lived agentic workflows in production, where a single run can last hours and fan out across dozens of subagents. Work spans durable execution, checkpointing and retries, LLM integration with guardrails, and tracing and cost attribution across services and two languages, with a backend and platform weighting in TypeScript and Node.js.

Restate · PostgreSQL · Google Cloud +7

• Cambridge
• Remote
• Entry level

Supports the design and implementation of AI, ML, GenAI and agentic AI solutions to optimise clinical trial design and execution across R&D. Builds GenAI applications for automated documentation such as protocols, clinical study reports and SAPs, and runs model evaluation and quality testing. Requires Python, SQL, LLM, prompt engineering and RAG familiarity.

GenAI · LLM · RAG

• London
• Remote
• Entry level

Supports the design and implementation of AI, ML, GenAI and agentic AI solutions to optimise clinical trial design and execution across R&D. Builds GenAI applications for automated clinical trial documentation such as protocols, study reports and SAPs, and evaluates model accuracy, relevance and consistency. Requires Python and SQL skills plus familiarity with LLMs, prompt engineering, RAG and cloud platforms.

GenAI · LLM · RAG