976 to 1,000 of 2,708 Machine Learning Jobs in London

Typescript. 3 years of experience with front-end frameworks, full-stack development, or API development. 1 year of experience with software design, architecture, and machine learning. 1 year of experience with agentic coding. Preferred qualifications: Master's degree or PhD in Engineering, Computer Science, or a related technical field. ...

third-party suppliers and multiple concurrent priorities will also be important. Exposure to Microsoft Fabric, Power BI, Power Platform, advanced analytics or AI/ML data solutions would be advantageous, as would Microsoft Azure certifications and experience within FMCG, Retail or a multinational organisation. Why Consider This Azure Data Platform ...

Artifactory, Nexus) and secure software supply chain practices. Knowledge of observability systems, telemetry frameworks, and performance optimization for build pipelines. Exposure to AI/ML-driven build acceleration and failure prediction tooling. Prior hands-on software development experience building customer-facing features. At BNY, our culture allows ...

Artifactory, Nexus) and secure software supply chain practices. Knowledge of observability systems, telemetry frameworks, and performance optimization for build pipelines. Exposure to AI/ML-driven build acceleration and failure prediction tooling. Prior hands-on software development experience building customer-facing features. At BNY, our culture allows ...

operational data according to sensitivity and security requirements. Designing and maintaining critical data delivery systems - encompassing both realtime data, historical data and AI/ML use-cases Collaboration with product owners and stakeholders to ensure data solutions align with business and regulatory requirements Capable of finding a balance between best ...

Typescript. 3 years of experience with front-end frameworks, full-stack development, or API development. 1 year of experience with software design, architecture, and machine learning. 1 year of experience with agentic coding. Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. ...

with each feature. About you: Qualifications and experience: Essential: Degree in computer science, software engineering or a related discipline, or demonstrably equivalent professional experience. ML operations capability: comfortable operating model-serving infrastructure and running established training and evaluation pipelines on Linux/GPU hardware process management, resource monitoring, versioned promote ...

public cloud environments (AWS, Azure, or GCP).Broad experience (in two or more) and understanding across the fields of data engineering, data warehousing, AI, ML, governance, transactional systems, app development, and streaming. Undergraduate degree (or higher) in a technical field such as Computer Science, Applied Mathematics, Engineering or similar. ...

entire technical stack, driving architectural decisions and mentoring others to ensure we ship scalable, high-performance systems that transform how our customers interact with Machine Learning. What you'll be doing: Leading the architecture and design of complex projects to ensure they are robust, scalable, and aligned with long ...

representing security requirements to non-security stakeholders. Working knowledge of cloud environments (Microsoft Azure and/or Amazon AWS) and the AI and ML services offered within those platforms, with the ability to assess security configurations, data handling behaviors, and integration risks. Experience partnering with development teams, data teams ...

managed services transitions and operating model transformations for global financial services clientsPublished thought leadership in SRE, platform engineering, or IT transformationExperience with AI/ML-driven operations (AIOps) and emerging automation technologiesITIL 4 Managing Professional or Strategic Leader certificationAbout usWe’re a global, team of innovators. Together, we harness engineering ...

methodologies. Knowledge of various analytical tools, including Qlikview, Tableau, and Access. Proficiency in data analytics tools (e.g., Python, SQL). Understanding of AI/ML concepts and technologies. Education Bachelor's or Master's degree in Finance, Engineering, Computer Science, or a related technical or quantitative discipline from ...

Protocol). Experience with MLOps/LLMOps tooling such as experiment tracking, model versioning, monitoring, evaluation/observability platforms, or CI/CD for ML and LLM systems. Experience implementing responsible-AI or AI-governance controls such as guardrails, human-in-the-loop oversight, and audit trails in production. Experience ...

Learning and large language models. Hands on experience across prompt engineering, agent development and evaluation frameworks. Demonstrated proficiency in Python AI/ML frameworks with the ability to write and review production-grade code across the full stack. A proven track record architecting and designing scalable solutions that ...

evaluation , implementing rigorous frameworks to continuously monitor, measure, and improve GenAI feature quality, accuracy, latency, and user satisfaction. , Collaborate with data scientists to productionise ML models and forecasting algorithms Your Skills Extensive background in Data Science Engineering, with a clear track record of principal‐level technical leadership. Hands‐on experience … building and shipping AI/ML products in production Deep practical experience with LLM‐based systems: RAG architectures, embedding pipelines, prompt and response logging, evaluation frameworks. Hands‐on expertise with vector databases, graph databases, and knowledge graphs End‐to‐end exposure in model lifecycle development, including extensive experience training ...

direct iteration with users. What We RequirePast experience building solutions with LLMs and a deep understanding of overall Gen AI landscape. Strong foundation in Machine Learning basics (Evaluation, Training, Problem Decomposition).Strong engineering background. Preferred fields include but are not limited to Computer Science, Mathematics, Software Engineering, Physics … Machine Learning. Strong coder with demonstrated proficiency in programming languages such as Python, Java, C++, TypeScript/JavaScript, or similar. Ability and interest in travelling up to 25%, as needed to client sites, but flexible based on personal preferences. Life at PalantirWe want every Palantirian to achieve their best ...

novel approaches such as graph networks, anomaly detection, and behavioural signals into production where they create real impact. Who you are End-to-end ML ownership across the full stack: data engineering, feature development, model design, training, low-latency production deployment, monitoring, and retraining. Strong instinct for when a model … ready for production and when it is not. Proven track record of building ML models and pipelines from scratch, not integrating or extending someone else's product or tooling. Experienced building real-time or near-real-time inference systems; batch pipelines alone are insufficient. Comfortable with large-scale datasets including ...

cutting edge of the field, with current research threads including: System Understanding: Interpretability, steering vectors, and the science of evaluations. Control & Alignment: Goal drift, machine unlearning, and uncertainty calibration. Societal Safeguards: Misinformation mitigation and robust deployment boundaries. We collaborate closely with the Faculty's wider AI safety team … labs, or evaluation roles. Deep knowledge of language models and generative AI architectures, including white-box techniques beyond API-level access. Strong foundation in machine learning fundamentals, particularly in robustness, explainability, or uncertainty estimation. Proficiency with deep learning frameworks like PyTorch and the Python skills required ...

conditioned on action. Run post-training: supervised fine-tuning onto target embodiments, and RL for robustness beyond demonstrations. Key Qualifications A PhD in robotics, machine learning, or computer vision with a robot learning focus, from the PhD alone or followed by industry experience. Publications at top venues … Deep experience with modern robot policy designs (VLA, WAM, diffusion), trained end to end rather than fine-tuned from a released checkpoint. Strong imitation learning fundamentals, and familiarity with RL fine-tuning of pretrained policies. Fluency with VLM backbones and how to adapt them for control. Expert Python ...

team with access to cutting‐edge multiomic and interventional datasets, advanced computational infrastructure, and deep interdisciplinary expertise, and a culture that embraces modern ML tooling, including agentic workflows, to accelerate research iteration. You will contribute advanced data analysis and domain expertise to challenge ML models that aim to predict … cohort design through to interpretation, so experiments are analytically tractable and pipelines maximise data value. Contribute to the evaluation framework that determines whether ML models capture meaningful biology: design metrics, held‐out benchmarks, and biological sanity checks. Collaborate closely with ML modellers to develop model architectures. Present findings and methodologies ...

enjoy building practical agentic tools and setting strong engineering standards, you will find meaningful ownership and growth here. As an Applied AI ML Lead Engineer, Vice President in the Applied AI and Machine Learning engineering team within Asset and Wealth Management, you will enhance, build, and deliver trusted ...

develops and deploys responsible AI solutions for clients across government, finance, retail, energy, life sciences, and defence. Задачи Set the technical direction for complex ML projects, balance trade-offs, and guide team priorities; Design, implement, and maintain reliable, scalable ML and software systems while justifying key architectural decisions; Define project ...

JPMorgan Chase's Chief Data & Analytics Office seeks an Applied AI ML Director - NLP/LLM and Graphs to apply cutting-edge machine learning methods to complex tasks such as NLP, graph analytics, and time-series predictions. You will collaborate with business, technology, product, legal, and compliance teams … deploy solutions into production. The role emphasizes deep learning expertise, agentic AI, and strong communication skills, in a highly collaborative setting across the firm. #J-18808-Ljbffr ...

complex business requirements into robust, scalable architectures on Google Cloud, operating at the intersection of technical depth and stakeholder collaboration. Working across AI and ML workloads, data platform design, and cloud migrations, you will act as a trusted technical voice for clients and a key partner to delivery teams. … client needs Define and design infrastructure strategies using IaC, containerisation, and CI/CD for repeatable, production-grade deployments Design and architect AI/ML and Agentic AI solutions using Google Cloud services such as Vertex AI, Model Garden, and Gemini Develop Agentic AI systems and intelligent automation workflows Design ...

trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance. At Tower … platformAssisting in development and optimizing large-scale parallel computation problems that requires large quantities of data shared across resourcesOptimizing the computational efficiency of existing machine learning based algorithms to drive higher performance and faster learning ratesDeveloping systems, interfaces and tools to historical market data and trading simulations ...