Artificial Intelligence Jobs

• New York, United States
• Hybrid
• US$200,000 – US$250,000 pa
• Senior

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Leads scoping and architecture design, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter to embed AI models on-site.

Python · PyTorch · Pandas +3

• Singapore
• Hybrid
• Lead

Develops high-fidelity multiphase CFD and DEM models for industrial bioprocess and chemical engineering applications, covering gas-liquid, solid-liquid, VOF and Euler-Euler/Euler-Lagrange approaches. Owns the full simulation pipeline from geometry clean-up and meshing to solver setup, HPC job scheduling and experimental validation, while building parametric CAD models and AI surrogate models to support design optimisation and customer-facing delivery.

Star-CCM+ · OpenFOAM · Fluent +5

• London
• Hybrid
• Senior · manages people
• Permanent

Owns validation strategy for ADAS and L2 autonomy functions, translating product, safety and regulatory requirements into test scenarios, metrics, coverage and acceptance criteria. Works hands-on with Python evaluation pipelines, simulation and SQL-based data analysis, spanning simulated and physical test environments. Open at senior IC or manager level, with close collaboration across Product, Safety and Release stakeholders.

Python · SQL

• 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 · manages people
• Permanent

Leads an infrastructure engineering team owning the full deployment lifecycle of AI products in live customer environments, from rollout to long-term operational health. Sets the infrastructure roadmap, SLAs/SLOs, and drives backend work on AI agents, evaluation tooling and automation across Kubernetes, Terraform and CI/CD. Bridges AI research and production while working cross-functionally with customers, GTM, product and security.

AWS · GCP · Azure +5

• United Kingdom
• Remote
• Mid-level
• Permanent

Owns the data infrastructure behind frontier AI models, building large-scale pipelines for collecting, filtering and transforming training datasets. Also trains classifiers, quality filters and labeling models, and designs curation strategies like deduplication and quality scoring. Builds tooling so researchers can explore and train on massive datasets quickly.

Kubernetes

• United Kingdom
• Remote
• Mid-level
• Permanent

Join the research team at an AI audio company, training state-of-the-art models across modalities and pushing existing models further through post-training, data curation and architectural improvements. You'll also design rigorous benchmarks and evaluations to determine whether new model iterations are genuinely better, working in lean autonomous teams with minimal bureaucracy.

GitHub

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

You will prototype and develop new ideas to improve Darktrace's cybersecurity services, balancing creativity with time constraints while collaborating with a cross-functional team of engineers, designers and strategists. Work spans rapid prototyping and structured platform development, with a primary focus on TypeScript alongside Docker and cloud environments.

Docker

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

Partners with developers and product teams to embed quality from the start, designing and maintaining automated test frameworks across API, UI, integration and regression layers. Builds scalable suites into CI/CD pipelines, drives shift-left testing, and contributes to test strategy, code reviews and architecture discussions.

Cypress · Playwright · pytest +7

• London
• Hybrid · 3 days in office
• Lead

Technically lead the Platform group, designing, operating and refining cloud infrastructure across research, development and production. Work spans GCP, Kubernetes, Docker, Terraform and Kapitan, plus CI/CD, observability and tooling, partnering with scientists, ML researchers and product teams. Reports to the Director of Engineering in a small, fast-moving team.

GCP · Kubernetes · Docker +7

• London
• Hybrid · 3 days in office
• Lead

Design and evolve a large-scale ML infrastructure platform that supports distributed training and inference workloads, working closely with research, engineering and product teams. The role also explores deploying agents to improve platform robustness and reliability, in a hybrid London setup requiring three office days a week.

Kubernetes · Google Cloud Platform · GCP

• Austin, United States
• Hybrid
• US$211,197 – US$257,901 pa
• Senior
• Permanent

Founding pre-sales role building Synthesia's North American Solutions Engineering function across Mountain, Central and West regions. Partners with AEs, Customer Success and Product Marketing on discovery, demos, POC scoping and technical solution design, while shaping the playbook, tooling and reusable assets as the team scales.

MEDDPICC · Command of the Message · SOC 2 +1

• Germany
• Hybrid · 2 days in office
• Senior
• Permanent

Founding presales role building Synthesia's Solutions Engineering function across DACH, partnering with Account Executives, Customer Success and Product Marketing on discovery, demos, POCs and technical solution design. You'll shape the playbook, tooling and reusable assets while acting as a trusted advisor on API, SDK, security and compliance topics, feeding field learnings back to Product.

LMS · HCM · CRM +2

• United Kingdom
• Remote
• Senior
• Permanent

Builds and scales products on top of FinLLM and other LLMs, engineering event-driven microservices, APIs, cloud-native AWS systems and React front-ends that bring AI into real financial workflows. Works closely with product and PhD-level AI specialists, using Node.js, TypeScript, NestJS and AI coding assistants in a remote-first team.

Node.js · TypeScript · React +11

• Switzerland
• Remote
• Senior

Develops performance optimizations in deep learning frameworks using JAX, contributing to JAX core components and driving peak performance on NVIDIA hardware. Works with AI researchers to build future-proof models and tooling that bridges numerical computing, simulation and deep learning research. Requires C/C++ and Python skills plus deep knowledge of ML framework internals and CPU/GPU architectures.

JAX · PyTorch · TensorFlow +4