2,201 to 2,225 of 2,755 Machine Learning Jobs in London

either side of the table. Strongly preferred: executive-level experience at an enterprise software vendor selling into the Fortune 500 (iPaaS, AI/ML, cloud platforms, data, ERP, or adjacent infrastructure). Also compelling: a customer-facing operator role in which you regularly represented your company's products, platform ...

discovery and expansion, not just top-of-funnel acquisition. Experience with open-source community strategy has shipped or grown an OSS project, ideally in ML/AI. Comfortable working in a hybrid PLG + SLG model and operating cross-functionally with teams whose roadmaps this role doesn't own. What ...

hackajob is partnering directly with Kingfisher to hire for this role. We're Kingfisher, A team made up of over 74,000 passionate people who bring Kingfisher - and all our other brands: B&Q, Screwfix ...

example Python, C#, JavaScript, Kotlin, Java or Go)Experience with Gen AI tools (such as LangGraph, CrewAI, Hugging Face or OpenAI APIs) and ML frameworks like PyTorch or TensorFlowStrong understanding of ML fundamentals (training, evaluation, deployment) and LLM-specific challenges such as prompt engineering, latency and cost optimisationExperience with cloud ...

team builds the foundational infrastructure. This infrastructure includes high-throughput streaming and cloud warehousing to automated data governance. It fuels clinical analytics, AI/ML innovations, and global data sharing. Why Join Us? Direct Impact at Scale: Promote the central data engine behind every Medidata application, directly accelerating clinical trials … data security. Product-Minded Engineering: Treat data as a first-class product, transforming static databases into high-value, reusable assets for internal AI/ML teams and external partners. Fuel Advanced AI/ML : Promote next-generation predictive modelling and clinical analytics by standardising and safeguarding complex healthcare datasets. What ...

agile team that designs, builds, and operates the services that make large language models usable at scale. This is an infrastructure-meets-ML role: you don't need to be an ML researcher, but you should be excited to learn how model architectures and inference constraints translate into real production ...

agile team that designs, builds, and operates the services that make large language models usable at scale. This is an infrastructure-meets-ML role: you don't need to be an ML researcher, but you should be excited to learn how model architectures and inference constraints translate into real production ...

fraud prevention solutions. Raise the team's collective bar through hands-on technical leadership and knowledge sharing. Proactively research and integrate latest developments in ML and payer fraud prevention to drive innovation at GoCardless. What excites youBeing a self-starter who thrives on taking a vague business problem and owning … beyond execution to help define the technical roadmap for Payer Fraud Prevention, ensuring we leverage the best tools for the job. Building production-grade ML models on a streamlined GCP and Vertex AI stack to drive fintech innovation. What excites usYou hold a degree (or PhD) in a STEM discipline ...

transform the way biomedical professionals carry out their research and day-to-day exploration. What you'll be doing· Design and implement ML/AI solutions end-to-end, from the idea and data exploration phase to deployment and monitoring, balancing cutting-edge techniques with pragmatism to deliver measurable impact. … reliable, maintainable, production-ready and can be readily adapted to future developments.· Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM-based solutions, and agentic solutions to balance trade-offs between speed, cost, complexity, interpretability, and performance.· Collaborate closely with product, design ...

structure we service. Next-Generation Platform Intelligence Building the AI foundations that make every future capability more powerful - predictive analytics, enterprise knowledge management, continuous learning models, and the intelligent infrastructure that underpins a truly AI-native Fund Services platform that compounds in value over time. What we'll need … Computer Science, Engineering, Data Science, or a related technical field Relevant experience across product development and engineering, with significant focus on AI/ML-driven products and heavy recent exposure to Generative AI Demonstrated ability to design, build, and scale complex software systems - including cloud architectures, distributed systems, and modern ...

catalyst for accountable growth, not a brake. What We Are Looking For Engineering & Technical Leadership Substantial experience leading software engineering, data, or AI/ML teams, typically 12+ years of relevant experience with several in a leadership capacity, delivering production-grade solutions at enterprise scale. Strong hands‐on foundations … example Python, SQL, cloud‐native platforms, data pipelines), enough to set technical direction credibly and make sound architecture decisions. Demonstrated experience with AI/ML technologies, including LLMs, Retrieval Augmented Generation (RAG), agentic workflows, Natural Language Processing (NLP), and predictive analytics, and the discipline to run them reliably in production. ...

software engineering experience, with strong fundamentals in system design, data structures, and clean code practices. Proven experience designing and shipping production-grade AI or ML-enabled software systems. Strong proficiency in Python, including building and shipping production backend services. Hands‐on experience building applications with LLMs such as Azure OpenAI … monitoring. Experience implementing responsible AI practices in a regulated environment, including audit trails, confidence scoring, and human‐in‐the‐loop controls. Background in traditional ML or data engineering, including feature pipelines, model training, and ETL, is preferred. MongoDB or other NoSQL database experience is preferred. Prior exposure to insurance domain ...

with information retrieval concepts (e.g., indexing, ranking, query understanding) Exposure to clickstream data, user behavior analytics, and event tracking systems Experience supporting evaluation of ML-based ranking or retrieval systems Familiarity with RAG systems or GenAI applications Why join us? Join our team and contribute to a culture of innovation … publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness ...

teams and documenting technical solutions. A proactive, self‐motivated approach to addressing issues and driving improvements in backend systems. A strong commitment to continuous learning and staying up‐to‐date with emerging technologies and industry best practices. Nice-to-Have Qualifications: Familiarity with message brokers such as Kafka … tools like Jira for managing tasks and sprint planning. Certifications in cloud technologies, such as AWS Certified Developer. Manage, host, and serve AI/ML models (MLOps), by ensuring their scalability, reliability, and performance in production environments. Location: Candidates based in Spain: flexible remote work, with availability to travel ...

Software Engineer – AI Enabled Engineering · UK We are seeking a skilled Java Software Engineer with a growing interest and demonstrated exposure to AI/ML integration. This role is primarily Java-centric — you will design and build cloud-native microservices on our BPA (Beyond Policy Administration) platform — with the expectation … leading global insurers and reinsurers. • A collaborative, innovation-driven culture with exposure to modern technologies and cloud-native architectures. • Professional development opportunities, certifications, and learning programs. • Competitive compensation and benefits package, aligned with experience and location. ...

systemsFamiliarity with information retrieval concepts (e.g., indexing, ranking, query understanding)Exposure to clickstream data, user behavior analytics, and event tracking systemsExperience supporting evaluation of ML-based ranking or retrieval systemsFamiliarity with RAG systems or GenAI applicationsWhy join us? Join our team and contribute to a culture of innovation, collaboration … publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness ...

full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data/metadata/knowledge platforms, and AI/ML and analysis platforms, all geared toward: Building a next-generation, metadata- and automation-driven data experience for GSK’s scientists, engineers, and decision-makers, increasing productivity … reducing time spent on “data mechanics” Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions ...

leadership on architecture decisions, system design, technology selection, and engineering standards across multiple initiatives. Mentor and develop engineers in engineering, system design, AI/ML technologies, and modern development practices. Evaluate emerging technologies and recommend adoption where they improve product capability, engineering efficiency, or client experience. Foster a culture … automated testing, observability, and secure software development. Strong programming skills in Python, with familiarity in C++, C#, or similar languages. Experience with AI/ML technologies and hands-on knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, or similar Generative AI technologies is highly ...

learning frameworks (Pytorch, JAX, TensorFlow). You can work on different layers of the stack from low-level training backends, data ingestion to ML/RL algorithmic design and implementation. You know when and where to be rigorous and slower versus when to break and iterate quickly. You have … Publications in top-tier AI conferences (e.g., NeurIPS, ICML, CVPR, ACL, ICCV, AAMAS, ...) Advanced degree (PhD or MSc) in a relevant field (e.g., ML, DL, NLP, CV) Experience with large-scale distributed training and inference (multi-node, large models, MoE, parallelism strategies, etc) Experience training models for computer ...

Join us to shape the future of data, analytics, and AI at JPMorganChase. As part of our Applied AI ML team, you will have the opportunity to work in dynamic squads focused on impactful products and projects. You'll collaborate with diverse teams, accelerate your career, and help deliver solutions … mindset, and passion for innovation. Your contributions will directly influence how we maximize the value of data globally. As a Vice President, Applied AI ML Lead in the Firmwide Chief Data Office's Applied AI ML team, you will design and deliver AI solutions that advance our data governance ...

bright, creative professionals with diverse perspectives and backgrounds. Where you come in: We are seeking an experienced and adaptable Senior Data Scientist , with strong ML Engineering skills , to join a nimble and best-in-class data team at The Beatport Group. The role will report to the Director of Intelligence … Engineering, and will share in the ownership and delivery of cutting edge, scalable ML models. Initial workstreams will likely include: Content Recommendation and Personalisation Search Optimisation Audio Modelling You will play a crucial role in transforming our data into genuinely useful product features that empower artists and connect DJs with ...

science capability that partners with stream-aligned teams. You'll report into the Data Science Team Manager and lead end‐to‐end DS/ML projects, shape standards, mentor teammates, and ship models into production, balancing quick wins with robust engineering. In particular, we are currently exploring ideas around using … marking consistency in a range of qualifications. Tech focus: Python and AWS (or equivalents in Azure or GCP), with hands‐on work across classical ML and modern LLM/RAG systems using services like Amazon SageMaker and Bedrock. What you'll doPartner with stakeholders across the business to explore high ...

agile team that designs, builds, and operates the services that make large language models usable at scale. This is an infrastructure-meets-ML role: you don't need to be an ML researcher, but you should be excited to learn how model architectures and inference constraints translate into real production ...

most successful games company in the world, and we're just getting started. The role is leading the Group data&ML teamThe team is a central function that works both with other central group functions like marketing and game solutions, and the game studios which are part of Tripledot. Within … team, you'll be working with other AI/ML Eng, Data engineers, ML Ops, Data scientists, analysts and product owners. Role OverviewWe are looking for a practical, commercially-minded, results-oriented person to collaborate with studios and group functions and lead AI/ML/Data initiatives that will ...

healing automation for known failure patterns, reducing human intervention and on-call burden by 50%+ Build comprehensive observability stacks (metrics, logs, traces) with ML-driven anomaly detection and AIOps capabilities Lead automated incident management: detection, triage, escalation, remediation, and post-incident review automation Drive DB automation: automated provisioning, release … deployment pipelines TECHNICAL SKILLS & EXPERTISE Expert-level observability: Prometheus, Grafana, ELK/OpenSearch, Jaeger/Zipkin, Datadog, or Dynatrace Strong experience with AIOps and ML-driven monitoring: PagerDuty, Moogsoft, BigPanda, or custom ML pipelines Deep knowledge of FMEA, fault tree analysis, and chaos engineering tools (Gremlin, LitmusChaos, Chaos Monkey) Database ...