1,351 to 1,375 of 3,256 Machine Learning Jobs in the UK

postgraduate or recent research background in computational psychiatry, psychometrics, or applied natural language processing, with a specific interest in psychological measurement rather than machine learning in the abstract. Another applied research or data role where you were responsible for the rigour behind someone else's substantive decisions, rather ...

technology suppliers, research partners, SaaS providers, cloud services and outsourced security providers. Establish practical cybersecurity guardrails for the safe adoption of AI, machine learning and emerging technologies, particularly where sensitive data, research information or intellectual property may be involved. Own, maintain and improve cybersecurity policies, SOPs and control ...

relentlessly resourceful to solve problems and find smarter solutions than the status quo Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting About the role We’re entering a once-in-a-company moment: a major ...

focused on building KYC/FinCrime as a configuration-driven product, refactoring and building new scalable microservice systems, and increasing automation using ML/AI where it genuinely improves decisioning, review quality, and operational efficiency — with safe fallbacks and clear observability. As a team that touches both regulatory requirements … other engineers and sharing best practices. You’ll inspire a high-performing team environment where ideas are shared, technical excellence is pursued, and continuous learning is embraced.Additional Information For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when ...

JPMorgan Chase & Co. invites applications for an elite Applied Innovation ML Engineering role within the Chief Data Analytics Office (CDAO) Technology group. The position focuses on building scalable ML solutions for software, cybersecurity, and infrastructure, partnering across business lines to deliver long-term AI-driven projects. Responsibilities include delivering production … ready ML products, maintaining data pipelines, and driving architectural governance for secure, high-quality code. #J-18808-Ljbffr ...

working closely with product leaders to understand the full product lifecycle and strategic considerations, and good knowledge of SaaS Product metrics. Understanding of machine learning concepts and experience with implementing predictive models to forecast product performance and user behavior. Being able to be hands on to unblock your ...

approach to discovering new pharmaceuticals. As a Solution Architect, you will champion the adoption of modern pharmaceutical development systems including High Performance Computation, AI & Machine Learning, Electronic Lab Notebooks, and Laboratory Execution systems to enable drug discovery and development in areas such as bioinformatics, computational chemistry, genomics ...

clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity ...

create new classes of devices for the defence and security sectors. As the world goes through a new industrial revolution powered by AI and ML, help lead the UK through it. You will work across the whole machine learning development lifecycle from initial concepts and architecture decisions through … anything in between. Requirements: Strong knowledge of Python and its use in machine learning including hands-on experience building products with modern ML frameworks such as TensorFlow and PyTorch. Broad knowledge of machine learning techniques across multiple domains and the ability to transition into new domains ...

team within AI Foundations. We build the shared platforms, harnesses, and guardrails that enable engineering and product teams to safely, reliably, and deterministically use machine learning and generative AI agents for internal systems and workflows across the business. This is a delivery‐focused team that sits ...

other experts within our supportive and collaborative tech community through knowledge-sharing and peer-level support, coaching and mentoring Deepen yourexpertisethrough oura culture of learning and growth –you’llhave budget to take courses (technical and non-technical training), plus gain certifications Responsibilities As aData Architectyou willhelp drive data … right task, youwill beexpectedtoarchitect solutionsforsomeoffollowing technologiesand capabilitiesto ensure scalable, high-performance applications: Multi-cloud,datawarehousingand datalakeplatforms Datamanipulation,integrationand ingestiontechnologies Programming/scriptinglanguages ML/AI frameworks Infrastructure & DevOpsconcepts andtooling, Semantic models and metrics layers Datagovernance tooling As a Principal Consultant, you will be expected to: Operate at a strategic ...

Guide and assist teams in supporting operational and shared platform needs, reducing friction in deployment pipelines and accelerating release cycles. Enable the tools and learning resources that shorten onboarding time for developers and teams aligning to cloud-readiness expectations. Own & Evolve Shared Development Infrastructure: Maintain and enhance the foundational … Excellence Mindset: Understanding of cloud readiness, reliability, and the operational disciplines that underpin a mature SaaS platform. Emerging Technology Awareness: Awareness of AI/ML operations and how they can improve efficiency across platform and delivery workflows. Stakeholder Influence & Communication: Influence Without Authority: Proven ability to align and motivate teams ...

clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity ...

related technical field is preferred. Key Skills and Competencies: Deep Technical Expertise: Profound understanding of cloud-native architectures (AWS, Azure, GCP), AI/ML fundamentals and MLOps, and API design principles (REST, GraphQL). Experience with AI SDKs and mobile device ecosystems (Android Enterprise) is highly desirable. Strategic Product Acumen … talent. We are committed to providing our employees with a benefits program that is comprehensive and competitive - including healthcare, wellness, inclusion networks, and continued learning and development offerings. We offer community service days, in addition to the traditional insurances, compensation, parental leave, employee assistance program and paid time ...

purpose-built for marketing, trained on real marketing workflows and deeply integrated with ad platforms, CRMs, brand assets, and analytics tools. As an ML Engineer, you’ll design, build, and ship production ML systems that power our core product and agent ecosystem - from real-time chat and workflow automation … autonomous agents like daily performance briefings and competitor tracking. What you’ll work on Develop and deploy ML/LLM systems for marketing-specific workflows (reporting, analysis, review, compliance) Build agentic systems with persistent memory, tool use, and workflow orchestration Integrate models with live data sources (Google Ads, GA4, Meta ...

cloud infrastructure. You will drive IaC strategy, build robust GitOps practices, and own CI/CD pipelines in Azure DevOps, supporting AI/ML platforms across AWS and Azure. Ideal candidates have deep Terraform expertise, experience with Kubernetes-based ML tooling, and a proven track record in high‐availability environments ...

unlock what that means for the products our customers rely on every day. This is a role for someone who wants to build ML systems that genuinely change how people buy and sell homes — not maintain models that gather dust. What You’ll Do Design, build, and deploy … machine learning pipelines — from data ingestion and feature engineering through to model serving and monitoring in production. Own the full lifecycle of ML models: evaluate, iterate, and retire them with the same rigour you bring to building them. Collaborate closely with product and engineering teams to frame business ...

Responsibilities Lead end-to-end delivery of complex, multi-team AI projects including distributed systems, platforms, and AI/ML solutions Drive alignment on technical strategy with bp strategy, trade-offs, and delivery priorities based on commercial impact for bp Manage dependencies across technical and business teams, platforms, and external … Proven experience of project management, technical program management, or related roles Proven experience leading large-scale, cross-team projects Familiarity with the AI/ML lifecycle (model training, deployment, monitoring, MLOps) and AI/ML-based products or platforms Familiarity with Agile & Waterfall techniques (i.e PMP, PMI-ACP, Scrum) Experience ...

using statistical rigor to compare alternatives and drive decisions. Collaborate with engineers, product managers, and analysts to translate ambiguous business problems into well‐scoped ML solutions, including data requirements, modeling approach, and success metrics. Apply strong data modeling, feature engineering, and model selection skills across multiple domains, ensuring models … robust, explainable, and performant at scale. Safely integrate and operate AI/ML‐enabled solutions that improve outcomes, including monitoring model performance, detecting degradation, and driving continuous improvements in production. Demonstrate familiarity with AI‐driven systems, tools, or workflows and applying AI/ML concepts to real‐world products, contributing ...

focuses on integrating AI capabilities into production systems, ensuring they are reliable, secure, and deliver measurable impact. What You’ll Do Integrate AI/ML components into applications and operational workflows Design and implement Retrieval-Augmented Generation (RAG) solutions Evaluate LLM performance, identify failure modes, and implement mitigation strategies Test … appropriate Collaborate with engineers, data scientists, and stakeholders to deliver production-ready AI solutions What You’ll Need Experience building or integrating AI/ML systems into real-world applications Strong understanding of LLMs, ML models, and core statistical concepts Experience evaluating AI systems and improving reliability and performance Ability ...

signal generation pipelines from data ingestion and feature engineering to model training and deployment - in collaboration with our trading and infrastructure teams. Responsibilities Develop ML-based alpha generation models using high-frequency order book and market microstructure data. Design and maintain data pipelines, preprocessing, and feature extraction workflows tailored … monitoring. Requirements Degree in Computer Science, Machine Learning, Applied Mathematics, or similar quantitative discipline. Strong programming skills in Python and familiarity with ML libraries. Proven track record applying ML/DL to real-world problems. Familiarity with time-series modeling, signal extraction, or high-frequency data. Experience ...

across the UK. Scope agentic AI projects directly with senior business stakeholders, then design, train and ship the systems that solve them. Pure Python, ML engineering and customer ownership in one role. Palindrome is the agentic operating system for modern wealth management. Our platform pairs always-on AI agents with … Forward Deployed Engineering is the function that turns Palindrome from product into production outcomes. You will sit at the intersection of customer, product and ML, scoping agentic AI projects directly with the customer, then designing, training, evaluating and shipping the systems that solve them. This is not a delivery role ...

radically transform Commodities Trading. This is a hands‐on Individual Contributor role. Required Qualifications 5-8+ years of experience building production AI/ML systems Modern Python proficiency with deep knowledge of the ecosystem (Pydantic, FastAPI, asyncio, type safety) Experience with modern AI frameworks (we currently favour Pydantic … Production experience maintaining human‐in‐the‐loop systems and AI monitoring/observability Strong fundamentals in AI/ML evaluation frameworks Experience building agentic systems including MCP, tool calling, memory systems, vector-based knowledge stores, guardrails In depth understanding of modern software design principles (e,g. microservices, event-driven architectures ...

Hopper is seeking a Lead, Finance Analytics & Enablement AI/ML to own the data warehouse, BI, GCP/AI optimization and Finance AI strategy. You will partner with executives and manage a small team to deliver a centralized, trusted data backbone across finance and business units. The role demands ...

escalables. Realizarás la documentación y seguimiento de modelos, evaluarás desempeño y propondrás mejoras, manteniéndote a la vanguardia de tendencias en analytics y ML, en un ambiente global con impacto en clientes. #J-18808-Ljbffr ...