Machine Learning Jobs

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

Build and deploy customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. The role spans rapid prototyping, backend development with Python/FastAPI microservices, and cloud deployment using Kubernetes, Terraform and AWS/Azure, with frequent on-site travel to customer sites.

PhysicsX · Singapore

Build and deploy customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. The role spans rapid prototyping, backend development of Python/FastAPI REST APIs and microservices, and cloud deployment using Kubernetes, Helm, Terraform and AWS/Azure. It suits someone who can grasp complex engineering problems across industries and own solutions end-to-end.

NVIDIA · Cambridge

Acts as the primary technical advisor to university research labs and faculty, embedding NVIDIA's frameworks and software stack into large-scale AI and HPC workloads. Drives joint research projects, delivers hands-on training and workshops, and feeds researcher needs back to engineering. Requires deep LLM lifecycle expertise across multi-node systems and around 30% travel.

NVIDIA · Reading

Acts as the primary technical contact for academic and research partners, helping integrate NVIDIA's accelerated computing stack into large language model and HPC workloads. Drives joint research projects, delivers hands-on training and workshops, and feeds researcher needs back to engineering. Requires deep multi-node LLM lifecycle expertise and involves around 30% travel.

Faculty · London

Lead technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging AI research and production. You'll build scalable ML infrastructure, champion safety-first frameworks and capability evaluations, advise senior client leadership, and mentor engineering talent while partnering with Frontier Labs on multi-agent tooling and AI governance.

Faculty · London

Lead the design, build and deployment of production-grade ML and LLM systems for national security and AI safety clients, including capability testing of frontier models. Act as a trusted technical advisor, define engineering standards for ML at scale, and mentor junior engineers while working with frontier labs on red teaming and evaluation.

Amazon · London

Builds and extends a data and ML platform that lets economists run analyses independently, automating pipelines and tooling with DBT, Python, Airflow, Spark, Iceberg and AWS services like Lambda, Bedrock and SageMaker. Works in a lean, no-on-call team without stand-ups or sprints, shaping technical direction for pricing, selection and delivery-speed projects.

Anthropic · London · £165,000 – £190,000 pa

You will partner with founders and engineers to architect LLM solutions on the Claude Developer Platform, running technical evaluations and guiding startups from discovery through deployment. The role blends deep AI engineering expertise with customer-facing work, feeding emerging use cases back to Product and Engineering teams.

Databricks · London

Expert-level technical leader owning the most complex enterprise customer engagements, driving consumption strategy and executive relationships as the definitive technical authority for banking and financial services accounts. Leads multi-workload platform architectures, enterprise migrations, real-time systems and AI/ML at scale, while mentoring junior architects and orchestrating cross-functional teams. Requires deep hands-on coding in Python and SQL plus expert Databricks platform knowledge.

Databricks · London

Expert-level technical leader owning the most complex enterprise customer engagements, driving consumption strategy and executive relationships as the definitive technical authority. Leads multi-workload platform architectures, enterprise migrations, real-time systems and AI/ML at scale, while mentoring junior architects and orchestrating cross-functional teams. Requires deep Databricks platform expertise, Python/SQL coding proficiency and a declared technical specialisation.

VIQU IT · London · £75,000 – £80,000 pa

Design and deliver deployable AI/ML models spanning forecasting, propensity, churn and customer segmentation, owning end-to-end workflows from feature creation to ML Ops deployment and monitoring. Architect bespoke datasets from structured and semi-structured sources, visualise results into decision tools, and mentor junior data scientists in a cloud-native, AI-first SaaS company.

Cohere · London

Owns the evaluation strategy for an enterprise AI workspace, building evals that capture agentic workflows, tool use and knowledge work. Translates user feedback, production failures and usage logs into continuous measurement, then feeds model failures and capability gaps back to central modelling teams. Sits between product, customer-facing and research teams rather than being pure research or product engineering.

Anthropic · London · £190,000 – £230,000 pa

Lead and grow a distributed EMEA team of Applied AI Architects, setting pre-sales standards and acting as technical lead on strategic digital-native accounts. The role involves use-case scoping, POCs, demos and ROI validation for Claude Enterprise, Claude Code and the Claude API, while guiding customers through GDPR, EU AI Act and data residency requirements alongside Sales, Product and Engineering.

Cohere · London

Founding Solutions Architect for the Nordics, owning the technical relationship with enterprise and government customers. Leads design and deployment of pilots, maps customer problems to AI solutions, and works with account executives, partners and product teams to drive adoption of LLM technology.

Wayve · London

Owns Wayve's end-to-end data strategy across the AI learning cycle, from foundation model training to production programmes, deciding what data matters and how it drives model performance. Leads a multidisciplinary Data organisation building the data flywheel: discovery, curation and enrichment of rare, safety-critical scenarios from very large real-world driving datasets. Works closely with Engineering, AI, Science, Validation, Product, Compute and Commercial leaders.