126 to 150 of 198 MLOps Jobs in London

Develop agentic workflows across areas like underwriting and claims Work closely with business stakeholders to define requirements and shape solutions Deploy models using modern MLOps practices (APIs, microservices, CI/CD, containers) Collaborate with engineers, product teams, and senior stakeholders across the business Tech stack Python & SQL (essential) GCP (preferred … flexible depending on experience) LLMs/GenAI/RAG/agentic frameworks (LangChain, LlamaIndex etc.) MLOps tools: Git, CI/CD, Docker, Kubernetes, APIs What you bring Core requirements 5+ years in data science/machine learning Strong foundation in traditional ML (e.g. XGBoost, regression, statistical modelling) Hands-on experience ...

Learning solutions that deliver measurable business impact. This is an exciting opportunity to work on cutting-edge projects involving Machine Learning, Deep Learning, NLP, MLOps, Cognitive Services, and Cloud AI Platforms . 🌟 About the Role As a Data Science Lead, you will be responsible for leading end-to-end data … Proof of Concepts (POCs). 🔹 Develop advanced NLP and Text Analytics solutions using modern frameworks and techniques. 🔹 Design and implement robust ML pipelines and MLOps practices for repeatable, scalable model deployment. 🔹 Work with Cognitive Services and AI offerings from cloud platforms such as AWS and Azure. 🔹 Develop and optimize machine ...

solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance and best practices * Translating business requirements into cloud-native AI and data architectures across Azure, AWS and GCP * Collaborating with technical and non-technical … stakeholders to deliver measurable business value * Supporting innovation initiatives, reusable assets, thought leadership and client proposals Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ...

/ML systems (from classical ML to GenAI) Developing robust, production-ready pipelines covering data ingestion, modelling, deployment, and monitoring Driving best-in-class MLOps practices, including CI/CD, model versioning, automated retraining, and rollback strategies Ensuring solutions are scalable, secure, and high-performing in real-world environments Defining … Demonstrated success delivering production-ready AI/ML solutions Hands-on experience with frameworks such as PyTorch, TensorFlow, or Scikit-Learn Solid understanding of MLOps and scalable deployment practices Experience with at least one major cloud platform (Azure, AWS, or GCP) Comfortable in client-facing environments, able to communicate complex ...

production environments Strong knowledge of cloud platforms, particularly: Azure (ML Studio, Azure ML, Data Factory, Synapse) Experience in AWS environments is beneficial Experience with MLOps practices and tools (CI/CD pipelines, model monitoring, versioning) Strong understanding of data engineering concepts (ETL pipelines, data lakes, feature engineering) Experience working with … problems Develop and maintain scalable data pipelines and feature engineering workflows Productionise data science models and integrate them into live services and platforms Implement MLOps best practices, including model versioning, monitoring, and CI/CD Collaborate with data scientists, analysts, and architects to design end-to-end ML solutions Ensure ...

supporting organisations as they move from strategy and experimentation through to enterprise deployment. You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes. Key responsibilities: Translating business objectives into … prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience designing APIs and integrating AI solutions into enterprise environments Strong understanding of modern data architectures and platform design ...

The Role We are seeking an experienced SC Cleared Data Engineer to design, build, and maintain secure, scalable data platforms and pipelines within a high-security environment. The successful candidate will work closely with data ...

Reports to : Director of Data Science & Engineering Job Purpose We are looking for a Data Engineer with Machine Learning experience to join our team. They will be responsible for maintaining and supporting the existing data ...

role involves designing and deploying ML models, collaborating with multidisciplinary teams, and mentoring junior engineers. The ideal candidate has experience in model lifecycle management, MLOps tooling, and Python. A salary of £63,823 plus benefits like 25 days annual leave and professional development opportunities will be offered. #J-18808-Ljbffr ...

learning engineering and an ability to influence the adoption of AI within the organization. The ideal candidate should have a strong background in Python, MLOps, and deep learning practices, with a focus on operational excellence and software quality. Opportunities for mentoring and collaborative work in a fast-paced environment await ...

development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations. Experience with developing and deploying Machine Learning Operations (MLOps) at scale. Experience with large‐scale foundational models and transformer‐based architecture (GenAI). Benefits Immigration support: The company provides support for your immigration process ...

Reliably fitting models with complex job dependency graphs Robustness in production, including validation and monitoring Qualifications An appreciation of good architecture and MLOPs best practice The ability to collaborate with, and influence, technical and non‐technical people A passion for end‐to‐end ownership of solutions, from articulation to delivery ...

supporting organisations as they move from strategy and experimentation through to enterprise deployment. You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes. Key responsibilities Translating business objectives into … prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience designing APIs and integrating AI solutions into enterprise environments Strong understanding of modern data architectures and platform design ...

implement system architecture for AI, data, and integration layers Build agentic AI workflows and knowledge-driven systems using modern LLM frameworks Implement robust MLOps pipelines for model training, deployment, monitoring, and governance Contribute directly to production code in Python and related AI/data tooling Support technical decision-making around …/Azure cloud platforms (including AI services such as Bedrock) Data engineering tools (e.g. AWS Glue or equivalent) NLP, embeddings, vector databases, RAG architectures MLOps tooling for model deployment and monitoring Experience with distributed data systems and APIs Required Skills & Experience Several years' experience in software engineering, data engineering ...

solve complex engineering and operational challenges. How you can make an impact Lead the design and evolution of our ML platform, infrastructure and MLOps capability Build and maintain scalable, reliable and secure systems for model training, testing, deployment, monitoring and lifecycle management Develop the infrastructure and tooling that enable … vision with operational rigour, and you’re motivated by delivering usable, secure, and elegant solutions to complex technical problems. Proven experience in a senior MLOps, ML Platform, ML Infrastructure, Platform Engineering or Machine Learning Systems role Strong hands-on background in software engineering and cloud infrastructure, ideally with direct experience ...

About us We are champions of rail, inspired to build a greener, more sustainable future of travel. Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey ...

Security £Up to £75,000 GBP Bonus Onsite WORKING Location: Manchester; Bristol; London , Central London, Greater London - United Kingdom Type: Permanent Data Scientist Specialist (MLOps & GenAI) Bristol Onsite/Hybrid Permanent Our client is a leading global technology and consulting organisation , recognised as one of Fortune's World's Most ...

collaboration across engineering, data science, and research to enhance drug discovery efforts through scalable ML solutions. The ideal candidate will have solid experience in MLOps, distributed systems, and a people-first approach to leadership. Compensation includes a competitive salary range of £96,052 to £127,237, along with bonuses ...

involves architecting cloud-native systems and leading engineering teams to deliver high-quality solutions using Azure and Databricks. Candidates should possess deep knowledge of MLOps strategies and have hands-on experience in building integrations. This hybrid position offers the opportunity to drive innovation and business impact while fostering a culture ...

massive datasets. This role includes mentoring and fostering a model-driven culture. The position combines a people-first mindset with deep technical skills in MLOps and distributed systems. A hybrid work model is in place, requiring office presence at least 50% of the time. #J-18808-Ljbffr ...

ability to drive adoption, influence behaviours, and deliver outcomes at pace Exposure to technologies, modern cloud platforms, customer data platforms, enterprise BI tooling, or MLOps governance environments would be highly advantageous. Why Join? This is an opportunity to define and shape governance strategy during a significant period of enterprise transformation. ...

design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning … data preprocessing pipelines Monitoring, optimising and maintaining deployed models for performance, cost and reliability Implementing explainability, fairness and bias-mitigation strategies Collaborating on MLOps pipelines, CI/CD workflows and production deployments Mentoring junior engineers and promoting best practices across the team Staying current with advances ...

Security £Up to £75,000 GBP Bonus Onsite WORKING Location: Manchester; Bristol; London , Central London, Greater London - United Kingdom Type: Permanent Data Scientist Specialist (MLOps & GenAI) Bristol | Onsite/Hybrid | Permanent Our client is a leading global technology and consulting organisation , recognised as one of Fortune's World's Most … programmes, only candidates holding active UK Developed Vetting (DV) clearance can be considered for this role . This opportunity sits at the forefront of MLOps, machine learning, and GenAI , working within a specialist team delivering high-impact solutions in complex, high-assurance environments. The position combines hands-on engineering with ...

rigorous evaluation protocols, including performance metrics, validation techniques, and safety checks. Ensure compliance with ethical guidelines and regulatory requirements .MLOps & Deployment: Guide development of MLOps pipelines for continuous training, testing, and deployment in cloud environments. Oversee infrastructure decisions to guarantee scalability, security, and maintainability . Mandatory Skill s:Master … frameworks (TensorFlow, PyTorch ).In‐depth knowledge of modern AI techniques: NLP, transformer networks, reinforcement learning, data engineering for A I.Extensive experience with AI/MLOps toolchains (model development, version control, CI/CD, automated deployment ).Familiarity with vector databases, agent orchestration frameworks, and evaluation librarie s.Strong analytical and mathematical skills ...

across fintech use cases. Architect the integration layer for how ~1,500 commercial team members interact with AI—including model governance, tooling, infrastructure, and MLOps frameworks. Lead and grow a high‐calibre team of Data Scientists, fostering a culture of rapid experimentation, technical excellence, and continuous learning. Drive innovation … Generative AI, Agentic AI, deep learning, and large‐scale ML deployment—staying ahead of the curve on foundational models, LLMs, and autonomous agents. Champion MLOps best practices, cloud‐native development (Azure preferred), and scalable production deployment pipelines. Collaborate cross‐functionally with Sales, Product, Engineering, and more to embed AI capabilities ...