Top Machine Learning Jobs in London

Manage a team of AI engineers to design, implement, and assess large-scale AI/ML pipelines, focusing on model training, evaluation, and data engineering.

Lead multiple engineering teams at Zego, focusing on technical excellence, product strategy, and cross-functional collaboration while mentoring team leaders.

As the Head of Engineering, you will lead engineering teams, drive technical strategy, and deliver AI solutions while collaborating cross-functionally.

Lead data architecture and engineering efforts, focusing on AWS solutions. Design data platforms, ensure compliance, and collaborate with cross-functional teams to align technical solutions with business needs.

As a Research Engineer, you will innovate and develop scalable data pipelines for LLM training, collaborate with experts, and continuously improve training data using machine learning techniques.

The role involves applying advanced machine learning methods, particularly in NLP and deep learning, to solve complex business challenges. Responsibilities include collaboration with teams, developing models, and driving firm-wide initiatives.

As a Lead Software Engineer, you'll design and maintain applications using Python and SQL, build data pipelines, analyze datasets, and architect AWS solutions to enhance cybersecurity.

The Tech Lead for Marketing Technology will lead technical teams, design scalable solutions, and ensure project execution in the gaming industry.

The Machine Learning Engineer will develop recommendation algorithms, collaborate with teams, mentor engineers, and improve algorithm performance based on user feedback.

The AI Ops and ML Engineer focuses on integrating AI and ML in network automation for GSK, optimizing network operations, incident management, and observability, while mentoring junior engineers and implementing best practices.

Join the ElevenLabs research team as a Machine Learning Researcher, focusing on creating data management systems and developing text-to-speech models, while exploring innovative machine learning approaches.

The AI Engineer will develop and deploy LLM services for a SaaS platform, optimizing risk assessment and improving customer workflows in the insurance industry.

The Senior Solutions Engineer will engage with clients to provide AI solutions, conduct technical demonstrations, and collaborate with product teams to meet customer needs.

The Machine Learning Engineer will create models and pipelines, collaborate on features, and evaluate AI/ML models to enhance Smartling's translation platform.

Lead Data Strategist will engage with customers, driving Data & AI transformation, developing technical assets, and strengthening relationships with C-suite leaders.

The Reserve Engineer provides customer service and maintains robotic hardware, addressing failures and assisting with deployments and field projects.

The Applied AI Research Scientist develops ML models/techniques, leads research projects, reviews literature, and explores data sources to enhance AI applications in architecture and engineering.