276 to 287 of 287 Machine Learning Jobs in Central London

make an impact from day one. What you will own Vision and roadmap for search, discovery, and AI-powered personalisation across the platform ML-driven recommendation engines, dynamic feeds, and ranking algorithms that surface the right content to the right member at the right moment Automation of high-volume workflows … when to Comfortable with ambiguity and able to bring structure to evolving, fast-moving environments Strong analytical foundation, at ease with data science concepts, ML features, and experimentation A communicator who can influence senior stakeholders and bridge technical and non-technical teams London-based and open to hybrid working What ...

make an impact from day one. What you will own Vision and roadmap for search, discovery, and AI-powered personalisation across the platform ML-driven recommendation engines, dynamic feeds, and ranking algorithms that surface the right content to the right member at the right moment Automation of high-volume workflows … when to Comfortable with ambiguity and able to bring structure to evolving, fast-moving environments Strong analytical foundation, at ease with data science concepts, ML features, and experimentation A communicator who can influence senior stakeholders and bridge technical and non-technical teams London-based and open to hybrid working What ...

RedCloud is seeking an experienced AI Lead to design, build, and maintain AI/ML capabilities that drive our products and enhance customer experiences. This hands-on leadership role involves leading a squad of AI engineers and data scientists while focusing on high-quality delivery and fostering a culture ...

across multiple client engagements • Translating complex AI concepts into clear, practical direction for business and technical audiences • Architecting and delivering production-grade AI solutions (ML + newer generative/agent-based approaches) • Acting as a trusted advisor in shaping AI roadmaps, solution design, and delivery approaches What matters for this … role: • Strong experience taking AI/ML solutions into production environments • Solid engineering foundations (Python and modern data/ML ecosystems) • Familiarity with cloud-based AI platforms and scalable data systems • Experience with deployment practices (automation, monitoring, reliability, etc.) • Ability to operate in ambiguity and guide decision-making with structure ...

across multiple client engagements • Translating complex AI concepts into clear, practical direction for business and technical audiences • Architecting and delivering production-grade AI solutions (ML + newer generative/agent-based approaches) • Acting as a trusted advisor in shaping AI roadmaps, solution design, and delivery approaches What matters for this … role: • Strong experience taking AI/ML solutions into production environments • Solid engineering foundations (Python and modern data/ML ecosystems) • Familiarity with cloud-based AI platforms and scalable data systems • Experience with deployment practices (automation, monitoring, reliability, etc.) • Ability to operate in ambiguity and guide decision-making with structure ...

solve real customer problems at scale. You will work at the intersection of product, engineering, data, and business to transform foundation models, LLMs, and ML capabilities into reliable, secure, and commercially viable applications. This role requires strong product judgment, technical fluency with modern AI stacks (LLMs, RAG, agents, evaluation frameworks … experimentation to production deployment, governance, and continuous optimization. Key Responsibilities: Product Strategy & Vision Define the product vision, roadmap, and success metrics for AI/ML initiatives Identify high-impact use cases where AI provides defensible value (automation, augmentation, insights) Translate business problems into AI capabilities and system designs Balance feasibility ...

solve real customer problems at scale. You will work at the intersection of product, engineering, data, and business to transform foundation models, LLMs, and ML capabilities into reliable, secure, and commercially viable applications. This role requires strong product judgment, technical fluency with modern AI stacks (LLMs, RAG, agents, evaluation frameworks … experimentation to production deployment, governance, and continuous optimization. Key Responsibilities: Product Strategy & Vision Define the product vision, roadmap, and success metrics for AI/ML initiatives Identify high-impact use cases where AI provides defensible value (automation, augmentation, insights) Translate business problems into AI capabilities and system designs Balance feasibility ...

scalability You have a clear point of view on how AI transforms product development, internal operations, and team structure You've implemented AI/ML in production, whether for content moderation, recommendations, NLP, or operational automation You're excited by agentic AI and understand how autonomous systems can handle workflows … sport, media tech, or startups with high fan or user emotion at their core Bonus: hands-on experience with LLMs, vector databases, real-time ML inference, or agentic frameworks This is a full-time role based in London. Our office is in Soho and we believe in the benefits ...

conversations. We don’t need you to write code. But you will discuss model architecture, deployment patterns, and computer vision use cases credibly with ML engineers and technical buyers. You will be expected to understand and consult on your client’s use-cases working hand in glove with Solution Engineering … facing-engineer-turned-commercial. Pure SaaS CS works too. We care about outcomes, not titles. Technically credible. You hold an architecture conversation with an ML engineer without bluffing. You translate technical value into business outcomes for budget owners. Prior experience with technical or developer-facing products (open source, APIs, ML ...

conversations. We don’t need you to write code. But you will discuss model architecture, deployment patterns, and computer vision use cases credibly with ML engineers and technical buyers. You will be expected to understand and consult on your client’s use-cases working hand in glove with Solution Engineering … facing-engineer-turned-commercial. Pure SaaS CS works too. We care about outcomes, not titles. Technically credible. You hold an architecture conversation with an ML engineer without bluffing. You translate technical value into business outcomes for budget owners. Prior experience with technical or developer-facing products (open source, APIs, ML ...

working acro ss:GPU/accelerated compute (NVIDIA ecosystem, CUDA, et c.)Cloud + virtualisation (orchestration, provisioning, multi-tenant environmen ts)AI/ML workloads — training, inference, production scal ingData centre & high-performance network ing Why this role stands out:Not your typical presales role - you’ll be shaping solutions … Background in pre-sales/solutions engineering/technical consu ltingExperience with cloud, AI infrastructure, or high-performance comp utingSolid understanding of AI/ML workloads and how they run in produ ctionStrong grasp of infrastructure fundamentals (compute, networking, virtualisa tion)Confident communicator — able to engage both technical and commercial ...

working acro ss:GPU/accelerated compute (NVIDIA ecosystem, CUDA, et c.)Cloud + virtualisation (orchestration, provisioning, multi-tenant environmen ts)AI/ML workloads — training, inference, production scal ingData centre & high-performance network ing Why this role stands out:Not your typical presales role - you’ll be shaping solutions … Background in pre-sales/solutions engineering/technical consu ltingExperience with cloud, AI infrastructure, or high-performance comp utingSolid understanding of AI/ML workloads and how they run in produ ctionStrong grasp of infrastructure fundamentals (compute, networking, virtualisa tion)Confident communicator — able to engage both technical and commercial ...