176 to 200 of 306 MLOps Jobs in England

infrastructure every pricing professional aspires to work with: High-quality, accessible data A fast, flexible rating algorithm deploy changes in hours Machine Learning Operations (MLOps) that enable fast, transparent, and controlled model development An operating model that gives complete autonomy to pricing professionals to dream up an idea ...

infrastructure every pricing professional aspires to work with: · High-quality, accessible data · A fast, flexible rating algorithm — deploy changes in hours · Machine Learning Operations (MLOps) that enable fast, transparent, and controlled model development · An operating model that gives complete autonomy to pricing professionals to dream up an idea ...

deep learning concepts, possibly in application to computer vision, NLP, or speech synthesis or recognition. Experience with data preprocessing and model evaluation. Familiarity with MLOps tools is a plus. Strong analytical skills and ability to work in a collaborative, fast‐paced environment. What We Offer Real ML work from ...

create real commercial leverage Skills and Experience Proven leadership in defining and delivering enterprise AI strategy, including GenAI Strong understanding of AI platforms, MLOps, and modern AI tooling (without needing to be hands-on) Experience translating AI opportunities into commercially impactful use cases at scale Exceptional communication, influence, and stakeholder ...

holding, and you’ll know when to ask for help Clear communication with both technical teammates and non‐technical stakeholders Experience with vision AI, MLOps, or cloud platforms is a bonus but not essential. What We Offer Up to £40,000 depending on experience Hybrid working — 3 days in Wolverhampton ...

biological plausibility, calibration, and model reliability Collaborating closely with computational biologists and research scientists to integrate models into discovery workflows Driving best practices across MLOps, experimentation infrastructure, and model deployment What They're Looking For Essential 5+ years experience building advanced machine learning systems in production Strong background in deep ...

plausibility, manufacturability, and therapeutic relevance Collaborating with computational immunologists, protein scientists, and wet-lab teams to validate model outputs Driving best practices across experimentation, MLOps, model deployment, and platform engineering Mentoring senior engineers and helping shape the long-term ML strategy of the company What They're Looking For Essential ...

experienced technology leader, with a proven track record of successfully leading AI/ML strategy and project delivery You bring a strong understanding of MLOps, with experience deploying commercially valuable AI applications within the financial services sector You have experience leading full‐stack technology teams, backed by a solid grasp ...

data platforms for analytics and AI/ML Deep Microsoft Azure expertise Hands‐on experience with Databricks, APIs, and integration platforms Strong understanding of MLOps and productionizing machine learning Experience leading and scaling engineering teams Tech stack: Azure, Databricks, Python, PySpark, SQL, JavaScript, Node, Bash THE ROLE … systems that support analytics, ML workloads, and real‐time operations Create API‐first integration layers for internal teams and external partners Implement MLOps best practices for model deployment and lifecycle management Lead exceptional teams Build, mentor, and scale high‐performing engineering teams Set standards for code quality, security, and performance ...

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 ...

Tune machine learning methods to best leverage our state-of-the-art processing capabilities Deploy and maintain machine learning methods in a DevOps/MLOps based machine learning environment Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards Your work will … Director of Technical Underwriting Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software. Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible. ...

/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 ...

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 ...

business can trust and use data with confidence. You’ll collaborate closely with colleagues in Data Engineering, Data Science, Pricing, Platform Engineering and MLOps, acting as a trusted partner and technical authority. Together, you’ll define clear standards for how data is structured, governed and consumed, helping the organisation grow … Terraform or Azure Bicep) to automate cloud deployments. CI/CD pipelines with Azure DevOps or GitHub Actions for automated deployment of data pipelines. MLOps best practices — MLflow, Databricks Model Serving, Feature Store. Knowledge of IFRS 17, BCBS 239, UK Data Protection Act and Solvency II compliance. Experience with pricing ...

business can trust and use data with confidence. You’ll collaborate closely with colleagues in Data Engineering, Data Science, Pricing, Platform Engineering and MLOps, acting as a trusted partner and technical authority. Together, you’ll define clear standards for how data is structured, governed and consumed, helping the organisation grow … Terraform or Azure Bicep) to automate cloud deployments. CI/CD pipelines with Azure DevOps or GitHub Actions for automated deployment of data pipelines. MLOps best practices — MLflow, Databricks Model Serving, Feature Store. Knowledge of IFRS 17, BCBS 239, UK Data Protection Act and Solvency II compliance. Experience with pricing ...

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 ...