551 to 575 of 4,929 Machine Learning Jobs in England

Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialisation in one area (e.g. real‐time/streaming, ML/AI, data governance, migrations) Ability to contribute to architecture discussions with senior technical stakeholders: whiteboarding, design reviews, and trade‐off analysis Track record of driving platform … Science, Engineering, or a quantitative discipline (or equivalent experience) Willingness to travel up to 30% as needed Nice to Have Databricks certifications (Data Engineer, ML, Platform) Cloud provider certifications at professional level (e.g. AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer; Azure Solutions Architect Expert; Google Professional Cloud ...

Proficiency in Shell or PowerShell scripting and Python Experience with Agile/Scrum practices Knowledge of Docker, Kubernetes, and AWS Exposure to AI/ML-powered tooling in software engineering or DevOps workflows Strong communication and stakeholder management skills Willingness to work in a hybrid model in London, UK Nice ...

passionate about designing and deploying intelligent machine learning solutions that drive business impact? Do you enjoy leading teams, building scalable ML systems, and turning complex data into innovative products and services? About the team: We are a software engineering team responsible for developing and supporting business-critical platforms … wider organisation. About the role: This position serves as a subject matter expert for Machine Learning Engineering, supporting production AI/ML, LLM/RAG, and agentic workflow capabilities for legal content products. In addition to writing code on complex systems, this position provides technical direction on architecture ...

degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or a related technical field. 2+ years of experience in software engineering, AI/ML engineering, backend development, or adjacent domains, with strong software engineering fundamentals and the ability to build production-grade systems. Strong proficiency in Python, plus experience … LangChain, AutoGen, or Semantic Kernel. Experience with video, audio, TV, or edge-device environments, especially where latency, cost, and hardware constraints matter. Familiarity with ML/DL frameworks such as PyTorch or TensorFlow. Research experience, paper implementation experience, or a habit of applying emerging GenAI techniques pragmatically to real problems. ...

human-in-the-loop controls. Evaluation: Using regression sweeps, canary testing and LLM-as-judge scoring to determine what is ready to ship. ML infrastructure: Building versioned training pipelines, model registries, scheduled jobs and deployments using Azure ML. What you’ll be responsible for Owning the development and continuous improvement … state management. Experience evaluating LLM applications using approaches such as gold datasets, regression testing, LLM-as-judge scoring and canary testing. Experience with cloud ML platforms - ideally Azure ML, Functions and Blob Storage - or the willingness to transfer your knowledge to Azure. Experience with Git-based workflows, CI/ ...

advanced analytics solutions into production. Strong Financial Services experience across banking, insurance or capital markets. Technical credibility across data engineering, data platforms, ML or Generative AI. Experience leading and developing high-performing technical/consulting teams. Strong consulting and commercial experience, including business development and selling work. Experience engaging senior ...

advanced analytics solutions into production . Strong Financial Services experience across banking, insurance or capital markets. Technical credibility across data engineering, data platforms, ML or Generative AI . Experience leading and developing high-performing technical/consulting teams. Strong consulting and commercial experience, including business development and selling work . ...

assumptions that need to hold, the confounders that need to be controlled for, and the experimental conditions that will make results actionable. AI/ML is the tool you bring to take those frameworks to a level of rigor, scale, and speed that wouldn't otherwise be possible - whether that … means building production-grade causal inference pipelines, designing ML-powered experiment analysis, or applying LLMs to accelerate how insights are generated and communicated. Responsibilities Design and implement marketing mix models and causal inference pipelines that quantify marketing effectiveness and inform budget allocation decisions Build and execute incrementality tests and translate ...

Experience influencing technical decisions and supporting capability growth. Experience with big data tools e.g. Spark, Hadoop, NiFi Exposure to Ansible and Terraform Understanding of ML algorithms and deployment ...

pools, but with a particular focus on financial & sales/revenue data is preferd. Desirable : More Data Science leaning background or want to explore ML/AI & data/predictive modelling strategies. Why you'll love this job A highly visible, hands-on role with real influence over data architecture ...

across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool … structured reasoning over enterprise data. Design and implement RAG pipelines, including chunking, embedding, indexing, retrieval, and reranking. Build and maintain integrations between retrieval and ML components and diverse enterprise data sources, vector databases, APIs, and services. Develop context retrieval systems that balance recall, precision, latency, and cost. Build evaluation frameworks ...

development SQL, databases & data platforms Data pipelines & ETL/ELT APIs & backend engineering CI/CD & production systems Analytics & modern data platforms AI/ML and emerging AI technologies It's a strong opportunity for someone early in their career who wants to develop into a well-rounded Full Stack ...

service integration into alerting, case management, and investigator workflows -Evaluation harnesses (golden datasets, regression tests, red-teaming scenarios, offline metrics) -Drive execution across engineering, ML engineering/data science, product, operations, compliance, model risk, architecture, cyber security, and technology controls -Create clear decision packs (options and trade-offs across risk ...

development 🗄️ SQL, databases & data platforms 🔄 Data pipelines & ETL/ELT 🔌 APIs & backend engineering 🚀 CI/CD & production systems 📊 Analytics & modern data platforms 🤖 AI/ML and emerging AI technologies It's a strong opportunity for someone early in their career who wants to develop into a well-rounded Full Stack ...

containers (Docker, Container Orchestration like Kubernetes/ECS/GKE). A genuine interest in and at least foundational experience with AI/ML concepts and technologies, demonstrating an eagerness to grow into a specialised AI Engineering role. Proven track record of delivering high‐quality work and driving forward best ...

fantastic team of technology experts. You will be responsible for designing, developing, and maintaining data pipelines and systems that enable data analysis and machine learning. You will also collaborate with data scientists, analysts, and other stakeholders to ensure data quality and reliability. Requirements Key Responsibilities: Develop Data Engineering solutions ...

comparable — including supervisor/multi-agent patterns. Strong AWS engineering background (Bedrock, Lambda, S3, IAM, CloudWatch); production operating experience on AWS-native AI/ML stacks. Demonstrated experience designing evaluation frameworks for non-deterministic AI outputs: golden datasets, regression testing, human review workflows, agent-level metrics. What We Offer: Competitive ...

Tech Lead level, with the ability to be both highly technical and an effective people manager Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience ...

Tech Lead level, with the ability to be both highly technical and an effective people manager Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience ...

with solution architecture, including creating architecture diagrams, data models, and technical specifications. Broad technical knowledge across analytics platforms, data engineering tools, and AI/ML technologies. Tool-agnostic mindset with ability to evaluate and recommend appropriate technologies for specific use cases. Excellent communication skills, with ability to explain complex technical ...

Tech Lead level, with the ability to be both highly technical and an effective people manager Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience ...

Your impact Secure, repeatable deployments across enterprise cloud environments. Increasingly, Gigaton deploy cloud workloads across GCP, AWS, and Azure, so that we can deploy ML‐Ops and data solutions inside our customer’s perimeter. You will help to design, simplify, and improve our entire stack so that we can meet ...

operate within our risk appetite. You will collaborate with stakeholders to develop and implement solutions that support our commercial goals, harnessing artificial intelligence and machine learning. Your work will contribute to a culture of integrity, innovation, and excellence. Job Responsibilities: Support and drive adherence to data risk management standards ...

Azure OpenAI OpenAI Services Kubernetes OpenShift MongoDB PostgreSQL SQL Server Neo4j Elastic Event Hub Service Bus Kafka Confluent GraphQL FinOps Platform Engineering AI/ML Operations (MLOps) Data Mesh Data Products Digital Twin The suitable candidate will need National Security Vetting (NSV) security clearance. They will preferably already hold ...

choices, production readiness and handover quality within the scope of each initiative. Skills & Experience: Essential Minimum 4+ years’ experience in software engineering, AI/ML workflow delivery or systems integration, with a demonstrable track record of full-stack delivery in production AI environments. Minimum 2+ years’ operating in a senior ...