Top Machine Learning Jobs in London

As a Principal Scientist in Biologics, you will shape Boltz Lab's platform by applying biological insights to machine learning models, guide model development, and influence product decisions for real-world biologics engineering.

As an Applied ML Engineer/Scientist, you'll adapt machine learning models to drug discovery problems, collaborating with domain experts and managing end-to-end modeling projects.

The MLOps Engineer will optimize, deploy, and operate large-scale machine learning models for Boltz Lab, ensuring efficient and reliable performance across distributed systems while collaborating with ML Researchers.

Lead end-to-end product lifecycle for insurance solutions using Salesforce and AI. Define roadmaps, translate customer needs into specs, drive cross-functional delivery, prioritize trade-offs, leverage data-driven insights, and partner with GTM teams to launch products that deliver measurable business impact.

The Sales Account Manager will manage and grow a defined portfolio of existing accounts in the maritime data sector, focusing on client retention, expansion opportunities, and team collaboration.

Lead architecture, design, and production deployment of scalable Generative AI and Machine Learning systems. Develop end-to-end GenAI features and integrate LLMs, optimizing and monitoring them within Anaplan's platform, ensuring high-quality AI solutions for business planning workflows.

The Principal Engineer will lead the design and deployment of AI systems, develop GenAI features, and integrate LLMs, requiring deep ML knowledge and software engineering skills.

Senior ML Engineer to productionise large-scale deep learning systems for outfit discovery: deploy batch and online models, build distributed GPU training, implement MLOps (data pipelines, CI/CD, containerisation, observability), drive technical direction, and mentor junior engineers.

Build, deploy, and maintain production-grade recommendation and ranking ML systems for personalization and discovery. Collaborate with data scientists to translate experiments into scalable batch and real-time services, monitor performance using behavioural signals, and contribute to shared ML platform and tooling.

Own production ML systems: re-architect POCs into scalable models (Churn, Next Best Action), deploy and optimize for low latency, monitor drift, build GenAI/RAG and vector DB infrastructure, run A/B tests, and translate insights for stakeholders while partnering with Data Engineers and Data Scientists.

The Social Commerce Manager oversees TikTok Shop brand storefronts, manages products, coordinates workflows, develops strategies, and collaborates cross-functionally to drive growth.

Support client engagements and design AI-enabled commerce solutions. Build full-stack prototypes to production, create agentic Python workflows, integrate LLMs and enterprise platforms, implement SQL/NoSQL data components, and follow DevSecOps within agile teams.

As a Product Manager for AML Screening at Napier, you will define the product roadmap and manage client and payment transaction screening to combat financial crime.

The Director, Product leads strategy and roadmap for key use cases, orchestrating teams to drive product growth and market adoption, while influencing company strategy and culture.

Lead the design and deployment of recommendation systems, mentor team members, collaborate across functions, and innovate using emerging ML techniques.

As a Senior Machine Learning Scientist, you'll improve customer outcomes through automated decisioning using ML and statistical modeling, focusing on credit risk modeling and collaborating with cross-functional teams.

The Machine Learning Engineer will develop AI systems for optimizing physical technologies, ensure high engineering standards, and push ML research boundaries while collaborating with domain experts.

The role involves guiding the Data Science team to develop search and recommendation systems, working with commercial teams to deliver user-focused products, and managing multiple projects related to data science implementation.

The Portfolio Lead will develop and manage the Data product roadmap, collaborate with stakeholders to enhance learning experiences, and leverage data insights to improve retention and performance in AI and tech upskilling.

As a Principal Machine Learning Engineer, you will design and develop scalable AI solutions, influencing company strategy and providing authoritative guidance on complex projects in the financial sector.

As a Lead Engineer, you'll integrate AI models into production, direct product development, collaborate in small teams, and apply visual AI to legal documents. You'll significantly impact real estate transactions by automating and improving due diligence processes.

As a Senior Engineer, you will integrate AI into real estate transactions, innovate product development, and solve complex multimodal reasoning problems.

The AI Analyst will collaborate with stakeholders to deliver AI solutions, validate models, improve deployment, and provide user training within the London office.

The VP of Engineering will lead the engineering teams overseeing cloud, platform, data, and application engineering, focusing on execution, reliability, and scalability of Hypervolt's systems while collaborating with hardware and firmware teams.

The Quantitative Researcher will research market anomalies, perform data processing, optimize strategies, and maintain portfolio trading systems.