Machine Learning Jobs

• London
• Hybrid
• Permanent

Design, build and operate shared infrastructure for language model access, agent runtimes and observability, taking projects from problem definition through technical design, deployment and ongoing operation. Partner with security, IT and engineering teams, and support adoption through troubleshooting, documentation and reusable patterns.

Kubernetes · MCP · RAG

• London
• Hybrid
• Lead · manages people
• Permanent

Builds and leads the technical programme management function for Wayve's AI Platform organisation, owning planning, prioritisation and execution across data and compute infrastructure, developer tooling, training technology and inference optimisation. Coaches a small TPM team, manages cross-team dependencies with ML, research, embedded and vendor partners, and drives measurable gains in developer velocity, compute efficiency and model performance.

Kubernetes · Ray · Flyte +6

• London
• Hybrid · 3 days in office
• Senior

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments, using Python, PyTorch, Pandas, fastAPI, Scipy and Kubeflow across cloud and on-prem. Leads scoping and architecture for data/ML systems, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter.

Python · PyTorch · Pandas +3

• London
• Remote
• Senior · manages people

Leads and scales the UK Forward Deployed AI Engineering team, delivering professional services engagements that help EMEA customers productionise GenAI and ML applications. Combines people leadership and hiring with executive customer advisory work, owning OKRs for revenue, utilisation and references while feeding voice-of-customer insight back into Product, R&D and GTM strategy.

Databricks · AWS · Azure +7

• London
• Senior

Owns the core write-path operations for Delta Lake, the open-source storage layer behind the Databricks Lakehouse, driving performance innovations like Low Shuffle Merge and Deletion Vectors. Involves low-level systems debugging, performance optimisation on large production clusters, architecture design, and technical leadership including mentoring and sprint planning.

Delta Lake · Databricks · Apache Iceberg +2

• London
• On-site
• Mid-level · manages people
• Permanent

Join the Preparedness team to anticipate and mitigate loss-of-control risks from increasingly capable AI systems, potentially culminating in recursive self-improvement. The role spans scalable oversight, automated auditing, monitorability testing, model behaviour science, and coordination/verification mechanisms, alternating between rigorous hypothesis-driven research and building interventions that impact production models.

• London
• On-site
• Mid-level
• Permanent

Researcher role focused on derisking frontier AI models by developing novel safety mitigations, drawing on interpretability, control, and alignment techniques. You will build and refine evaluations of emerging risks, design red-teaming pipelines, and set research directions, collaborating closely with experts in misalignment, cybersecurity, and biology.

• Oxford
• Hybrid
• £81,322 – £112,488 pa
• Lead · manages people
• Permanent

Dual role combining line management of a growing ML engineering team with hands-on technical delivery across multiple client engagements. You'll shape ML engineering practice, lead multidisciplinary teams, oversee solution design and quality assurance, and support pre-sales and use case discovery alongside commercial teams.

• London
• £80,000 – £105,000 pa

Hands-on engineering role designing, building and supporting production-grade AI solutions in a professional services environment. You will work with stakeholders to identify use cases, develop AI applications and agents using Microsoft technologies such as Copilot Studio and Azure AI Foundry, and ensure solutions are secure, auditable and compliant with GDPR and the EU AI Act.

Microsoft Copilot Studio · Azure AI Foundry · Azure DevOps

• Manchester
• Senior · manages people

Lead technical delivery of AI, machine learning and data science solutions for major financial services clients, including architecture design, production model deployment and mentoring small teams of data scientists. The client-facing role also involves senior stakeholder engagement, business development and thought leadership, using Python, SQL, Pandas, Scikit-Learn and Spark, with LLM, prompt engineering and RAG knowledge advantageous.

Pandas · Scikit-Learn · Spark

• Manchester

The OpportunityA leading financial consultancy is seeking a Senior AI & ML Engineer to lead the design, development and deployment of cutting-edge AI, Machine Learning and Generative AI solutions. You'll play a key role in shaping technical strategy, building production-grade…

• London
• Hybrid
• £50,000 – £60,000 pa
• Mid-level

Design, build and deploy scalable data pipelines on the Databricks Lakehouse Platform, working across the full engineering lifecycle from requirements gathering to deployment and optimisation. Build data models supporting reporting, analytics, ML and AI use cases, and implement governance and data quality practices within a consulting team delivering enterprise-scale platforms.

Databricks · Delta Lake · Azure +2

• Abingdon
• Hybrid · 4 days in office
• US$200,000 – US$225,000 pa
• Mid-level

Build scalable data platforms, pipelines and ML infrastructure, and deploy production AI solutions including LLMs, RAG systems and AI agents. Work in a small, highly visible team partnering with investment and operational stakeholders, owning projects end-to-end from design through production and driving architecture decisions.

Databricks · Spark · Kafka +2

• Royston
• £58,000 – £60,000 pa
• Senior

Owns AI security initiatives within a Cyber Security and Compliance team, evaluating and integrating AI security tooling and defending against threats like prompt injection, data leakage and model poisoning. Also builds AI-driven detection, vulnerability management and incident response, running threat modelling and adversarial testing of AI systems.

OWASP Top 10 for LLM Applications · MITRE ATLAS · NIST AI RMF +1

• London
• Hybrid
• £60,000 – £85,000 pa

Builds next-generation AI products for knowledge discovery, intelligent search and scientific insight generation, working hands-on with LLMs, RAG, semantic search, NLP and embeddings. Also develops agentic AI workflows with LangGraph and LangChain, and takes models into production via MLOps, within a hybrid London team serving the life science industry.

LangGraph · LangChain