1,051 to 1,075 of 1,295 Machine Learning Jobs in the UK

talent as the team grows. Ideal candidate credentials Proven sales leadership experience building and managing sales teams in high-growth SaaS or AI/ML-centric software companies. Deep understanding of the EMEA market with proven ability to grow business in the region. Track record of meeting/exceeding revenue ...

commerce, or B2B platforms at scale. Strong experience with API integration, microservices, and third-party service orchestration. Hands‐on exposure to AI/ML technologies and cloud-based AI integrations. Deep understanding of scalable architecture, distributed systems, and modern database design. Demonstrated ability to deliver robust, production-level technology ...

Software Roots: A strong foundational background in embedded software is required, alongside the technical breadth to converse fluently across DSP, FPGA, and AI/ML domains. Proven Formal Management: Direct experience acting as a formal line manager for a team, handling appraisals and performance development. Experience managing other managers ...

added advantage IT Services & Transformation Selling (must ‐ have) The candidate must be able to sell: Digital engineering Cloud migration/modernization AI/ML use cases (personalization, pricing, forecasting, chatbot/guest journey automation) Testing, integration, platform engineering Managed services & long‐term transformation programs Ability to manage 6–18‐month ...

development Exposure to tooling such as Terraform, APIs, or CI/CD pipelines (desirable) Experience working in Business Intelligence/analytics environments AI/ML Exposure (Essential) Candidates must demonstrate practical exposure to AI/ML, such as: Working with cloud-based AI services (e.g. AWS Bedrock or similar) Supporting … enabled data products or workflows Understanding generative AI concepts, including prompt engineering Exposure to ML pipelines or collaboration with Data Science teams (This does not need to be a core specialism but must be clearly evidenced.) Experience Required Typically 4-8+ years' experience in data engineering/BI roles ...

driven recommendations (e.g., MAP efficiency, allocation optimisation) and champion their use in business processes* Drive adoption of automation & AI. Lead AI/ML pilot projects, demonstrate tangible value and promote scaling of successful models* Collaborate with data‐engineering, data‐science and algorithm teams to innovate data sourcing, management and product … margin* Ability to prioritise dynamically in a fast‐paced, global environment* Bachelor’s degree in a quantitative or technical discipline* Experience deploying AI/ML solutions at scale (recommendation engines, demand forecasting, etc.)* Familiarity with automation/orchestration platforms (Airflow, Prefect) and MLOps tooling* Prior success influencing global data‐culture ...

lead a transformation mandate: move a legacy, on-prem supply chain platform to a cloud-native, composable SaaS architecture and embed AI/ML and generative AI across the product suite. The role is based in EMEA (Paris headquarters) and includes global engineering leadership and client-facing responsibilities. Key Responsibilities … analytics). Architect transformation from monolithic legacy systems to composable, API-first, cloud-native SaaS using microservices and event-driven design. Embed AI/ML as a foundational design principle and integrate generative AI/LLMs for copilots, natural language interfaces, autonomous workflows, and agentic capabilities. Own technical due diligence ...

While the initial project will involve TypeScript-focused development, the company is open to engineers from strong Java or Python backgrounds who are comfortable learning new technologies and working across a modern engineering stack. This role would particularly suit someone who enjoys solving complex engineering challenges, working independently … modern frontend frameworks Exposure to GraphQL APIs Experience with Terraform, Docker, or infrastructure-as-code tooling Familiarity with data engineering, analytics, or AI/ML-driven systems What's in it for you Join at an early stage of a fast-growing engineering consultancy Opportunity to become a foundational hire ...

that enhances governance, operations, and investment on a global scale. At Quantios, we are committed to fostering a diverse and inclusive workplace where creativity, learning, and collaboration drive success. As a Data Architect at Quantios, you will be responsible for designing the enterprise data architecture underpinning Quantios Insights … governance tools (Purview, Unity Catalog, Snowflake Governance, Fabric Governance). Experience designing data platforms to support analytics, BI, operational reporting, and AI/ML workloads. Understanding of LLM/RAG data preparation, unstructured data processing, and vectorisation workflows is advantageous. Strong communication skills with the ability to collaborate with engineering ...

beyond proof of concept into secure, production-grade deployment. The role: - Design AI and GenAI architecture strategies and roadmaps - Build scalable AI/ML and Agentic AI platforms - Work across LLMs, RAG, embeddings and semantic search - Support AI deployment, governance and integration patterns - Collaborate with engineering, data, DevOps and business … Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing enterprise AI or ML architectures - Strong grasp of cloud and modern data platforms - Exposure to scalable AI deployment and integration patterns - Financial Services or regulated industry experience (essential) - Strong ...

Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps … frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong ...

Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps … frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong ...

Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps … frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong ...

deployment across regulated financial environments. Key Responsibilities Design AI and GenAI architecture strategies and roadmaps that align with enterprise objectives. Build scalable AI/ML and Agentic AI platforms, working across large language models (LLMs), retrieval-augmented generation (RAG), embeddings, and semantic search. Support AI deployment, governance, and integration patterns … vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes, and GPU infrastructure. What We're Looking For Proven experience designing enterprise AI or ML architectures, with a strong understanding of cloud and modern data platforms. Demonstrable exposure to scalable AI deployment and integration patterns is essential, as is experience ...

lean development processes, engineering metrics (DORA, SPACE, etc.), and delivery predictability while maintaining velocity.Innovation & Technology : Stay ahead of industry trends (cloud-native, AI/ML, microservices, etc.) and evaluate new technologies that can drive business value.Risk & Compliance : Oversee technical risk management, data privacy, security standards, and regulatory compliance (SOC2, GDPR … concepts for non-technical executives.Strategic thinking combined with strong execution and operational rigor.Data-driven decision making using engineering metrics and KPIs.Experience with AI/ML integration or modern frontend/mobile stacks is a plus.What Success Looks LikeEngineering organization consistently delivers high-impact features on time with high quality.Low employee ...

development processes, engineering metrics (DORA, SPACE, etc.), and delivery predictability while maintaining velocity. Innovation & Technology: Stay ahead of industry trends (cloud‐native, AI/ML, microservices, etc.) and evaluate new technologies that can drive business value. Risk & Compliance: Oversee technical risk management, data privacy, security standards, and regulatory compliance (SOC2 … technical executives. Strategic thinking combined with strong execution and operational rigor. Data‐driven decision making using engineering metrics and KPIs. Experience with AI/ML integration or modern frontend/mobile stacks is a plus. What Success Looks Like Engineering organization consistently delivers high‐impact features on time with high ...

integration architecture, covering API management, event-driven patterns (Kafka, EventBridge), messaging (JMS, MQ), ETL/ELT pipelines, microservices and service mesh topologies. Champion AI, ML and agentic automation opportunities within the trading technology estate including intelligent scheduling, anomaly detection, automated P&L attribution, predictive maintenance and agentic workflow orchestration (e.g. … migration planning. Working knowledge of Foundry (Palantir) or equivalent analytical platforms for downstream data consumption, operational analytics and decision support. Experience architecting AI/ML and agentic automation solutions within trading technology estates, including LLM integration, RAG patterns, intelligent scheduling and predictive analytics. Familiarity with Agile/SAFe delivery frameworks ...

signal processing (e.g. MEMS microphones, accelerometers) Develop RF communication systems (LoRa/LPWAN, mesh networking) Implement secure communications (encryption, authentication, secure boot) Deploy optimised machine learning models on embedded devices Essential Experience Strong embedded C/C++ development experience Full product lifecycle … experience (concept to production) Low-power system design expertise Sensor data processing and RF communications (LoRa or similar) Embedded security and debugging skills Desirable ML for acoustic detection MEMS microphone systems OTA updates and noise mitigation Start-up experience If you're looking to build intelligent, low-power sensing systems ...

data in real-time, the structuring, storage and processing of that data for insight, to the usage of the data in event driven applications, ML and AI. As a Senior Manager Architect in Data you will be an experienced technical leader bringing business, industry and deep technical understanding to shape … specific expertise in Distributed Data Processing architectures (Spark, PySpark, Python, Airflow), ELT data processing underpinning Data LakeHouses and Data Products for scaled use within ML & AI Expertise in Streaming Data, Event Driven Design, Data Governance & the AWS Cloud Technology stack (e.g. Glue, ServerLess, DynamoDB) A track record in leading ...

help our users know their body better. The job We are looking for a Senior Software Engineer with deep expertise in AI/ML infrastructure to join our AI Platform team and help build the GenAI platform that powers every AI feature at Flo. You will bridge core infrastructure, data … directly with technology partners on pre-release capabilities Experience and Skills Must have Engineering maturity: 7+ years of software engineering, 4+ years focused on ML/AI platforms LLM experience: recent hands‐on work with at least one of: fine‐tuning, prompt engineering, LLM evaluation, or model serving Technical stack ...

engineers and researchers to develop and enhance systems that respond intelligently to organizational needs. The role demands a strong background in applied research and machine learning, encouraging publication and ownership of significant scientific projects. #J-18808-Ljbffr ...

vision, strategy and roadmap for Orchestration. This requires: Defining the multi-year vision for our orchestration infrastructure to move from static rules to dynamic, machine-learning routing - and working with your engineers and analysts to deliver this vision. Ensuring our payments are fully optimised to be routed between ...

robust and explosive DataOps business. Series C funded (raised over $60m this year ). They have built a product that leans into blending machine learning models and data annotation to help businesses save time and money! What You’ll Get This is a key hire ...

driven initiatives. * This role will suit someone with a strong foundation in AWS data engineering and BI, alongside practical exposure to AI/ML concepts or tools. * Design, build and optimise data pipelines and data platform components within AWS * Support and enhance Business Intelligence reporting and analytics capabilities * Contribute … services (e.g. AWS Bedrock or similar) * Supporting AI-enabled data products or workflows * Understanding of generative AI/prompt engineering concepts * Exposure to ML pipelines or collaborating with Data Science teams * Typically 4-8+ years' experience in data engineering/BI roles * Proven experience delivering AWS-based data solutions ...

metrics that drive engineering decisions anddemonstrateplatform health to stakeholders Champion AI and modern data tooling —you'llpush the boundaries ofwhat'spossible, with hands-on ML product experiencerequiredand LLMexpertisea serious bonus. Join us on a mission to become the best data company in telematics. If you're ambitious, passionate about data … data products Advanced Python (PySparkor Polars preferred) and SQL across multipleflavours— comfortable owning and evolving live production codebases Hands-on experience building and shipping ML products, not just prototyping Deep familiarity with Azure Data Lake and file-based storage architectures Strong Git discipline and version control best practices A genuine ...