Artificial Intelligence Jobs

NVIDIA · Italy

Engage directly with customers and partners to architect, validate and operate InfiniBand, RoCE and NVLink fabrics underpinning large GPU estates, owning the fabric lifecycle from Day 1 acceptance through Day 2 operations. Work tool-agnostically across Cumulus Linux, SONiC, Spectrum-X, DOCA/DPU, Kubernetes and Prometheus/Grafana, acting as technical lead for assigned accounts.

NVIDIA · Courbevoie, France

Engages directly with customers and partners to architect and validate large-scale GPU-accelerated HPC/AI platforms, spanning hardware handover through Day 2 production stability. Works tool-agnostically across upstream Kubernetes, KubeVirt, Slurm and observability stacks, owning cluster-wide validation, burn-in and fleet reliability targets.

PhysicsX · New York, United States · US$150,000 – US$250,000 pa

Builds and deploys customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, RESTful APIs in Python (FastAPI), microservices, and cloud deployment with Kubernetes, Helm, Terraform and AWS/Azure, plus 3-4 weeks of travel per quarter to customer sites.

PhysicsX · Singapore

First technical responder for enterprise and internal platform users, owning issues from triage and first-pass investigation through resolution or escalation to Product, SRE, FDSE or Deployment Engineering. Debugs inside Kubernetes clusters using Linux, Helm, GitOps (Argo CD) and cloud fundamentals, with fixes delivered via reviewed pull requests. Also builds runbooks and shapes a newly forming support function across SaaS, VPC and air-gapped deployments.

Anthropic · London · £165,000 – £230,000 pa

Leads delivery of custom agentic AI solutions for enterprise customers, owning engagements from signed SOW through production deployment. Drives delivery plans, product scoping, stakeholder relationships and ROI measurement while pressure-testing technical decisions alongside Forward Deployed Engineers. Also codifies reusable delivery patterns for an emerging function, with up to 25-50% travel to customer sites.

Wayve · London

Post-train, distill and evaluate GAIA-family large video diffusion world models for synthetic driving data, covering embodiment and pose transfer. Own large-scale GPU generation pipelines and land synthetic data into the driving-model training stack, working between ML research and platform engineering.

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.

Infused Solutions · London · £65,000 – £75,000 pa

Senior AI EngineerLocation: Remote (UK) or Hybrid - London (1 days per week in the office if London-based)Salary: £65,000 - £75,000 + Excellent BenefitsJob Type: PermanentPlease note: Applicants must have the right to work in the UK. Unfortunately, visa sponsorship...

Scale AI · London

Sets standards for responsible AI, model governance and production MLOps across a public sector team, and builds or validates the highest-risk parts of strategic AI systems. Acts as senior technical partner to client leadership, leads severe incident resolution, and coaches other applied AI engineers. Requires deep production AI/ML ownership and experience with regulated, sovereign or on-premise deployments.

The Alan Turing Institute · London · £96,000 – £115,000 pa

Provides scientific and strategic leadership for the AI for Physical Systems research area, shaping a portfolio spanning probabilistic modelling, uncertainty quantification, efficient architectures and physics-informed machine learning. Leads a multidisciplinary team of researchers and engineers, taking methods from foundational research through to deployment on real-world resilience challenges, and builds collaborations across academia, government and industry.

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.

Luminance · Cambridge

Designs and develops the core AI platform, building large-scale Python codebases and web-hosted services that power the company's software architecture. Works across the Python ecosystem, including Flask, Requests, NumPy and PyTorch, with scope to lead technical direction or teams. Open to graduates as well as experienced engineers.

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.

OpenAI · London

Hands-on engineering partner to international public-sector customers, delivering scoped GenAI and agentic use cases from mission need through architecture, evaluations, production and handoff. Works with government agencies, systems integrators and cloud providers on data residency, sovereign and regulated deployments, building prototypes on model APIs and Codex while feeding insights back to Product and Research.

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.