101 to 125 of 143 MLOps Jobs in England

following predictive modelling techniques; GBMs, Elastic Net GLMs, GAMs, Logistic Regression, Random Forests, Decision Trees, Neural Nets and Clustering Experience in DevOps, or other MLOps and ML Lifecycle stacks Experience with Docker and Kubernetes Experience in creating production grade coding Experience in programming languages (eg Python, PySpark ...

discovered and developed. We’re looking for senior candidates with deep expertise in: • Deep learning and modern ML systems • Distributed training and GPU infrastructure • MLOps, deployment, and reliability at scale • Biomedical, genomics, or drug discovery ML Requirements 7+ years relevant post PhD experience Experience productionising foundation models and model components ...

personal to all of us.” – Julie Sweet, Accenture CEO. We are a dynamic team of specialists in Data Science, Data Engineering, and MLOps, dedicated to delivering cutting-edge AI solutions within secure government and defence environments. Join us to be part of an inclusive and collaborative environment where innovation thrives ...

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 ...

practices across their ML and data setup, ensuring it is ready to support multiple enterprise deployments. Key responsibilities: * Audit current ML architecture, pipelines, and MLOps practices * Identify gaps in documentation, reproducibility, and scalability * Introduce clear structure across model development, versioning, and deployment * Improve training and retraining workflows * Strengthen model monitoring … Python and hands-on ML engineering experience * Proven experience in productionising ML systems end-to-end * Experience auditing and improving existing ML setups * Strong MLOps experience (model versioning, monitoring, CI/CD) * Experience working with data pipelines (ETL/ELT, Spark or similar) * Comfortable working with messy, real-world data ...

develop intelligent systems and tools Collaborating with cross-functional teams to integrate AI into production environments Conducting research, experimentation, and rapid prototyping Implementing MLOps best practices (CI/CD, monitoring, retraining pipelines) Translating business and stakeholder needs into scalable technical solutions Continuously improving AI/ML systems, frameworks, and performance … Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker, CI/CD, and version control ...

develop intelligent systems and tools Collaborating with cross-functional teams to integrate AI into production environments Conducting research, experimentation, and rapid prototyping Implementing MLOps best practices (CI/CD, monitoring, retraining pipelines) Translating business and stakeholder needs into scalable technical solutions Continuously improving AI/ML systems, frameworks, and performance … Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker, CI/CD, and version control ...

ready, with scalable infrastructure and clean, well-structured data pipelines Collaborate with data science and analytics teams to enable model deployment, automation, and MLOps best practices Promote innovation in generative AI, predictive analytics, and real-time decision support Align data architecture with security, compliance, and data governance requirements Lead … modern data integration tools. Excellent knowledge of Python, SQL, PowerQuery (M), and preferably Scala or PySpark Working knowledge with enterprise architecture frameworks (e.g., TOGAF), MLOps, and BI tools like Power BI and QuickSight Experience of generative AI platforms (e.g., Amazon Bedrock, Anthropic) Familiarity with infrastructure as code (Terraform), CI/ ...

120k – 150k GenAI/Agentic AI – Brighton (Hybrid) – AI-native Scale-up GenAI | Agentic AI | Machine Learning | Python | PyTorch | AI Strategy | LLMs | RAG | MLOps | Leadership |Do you want to lead AI at the core of a truly AI-native business building the next generation of virtual sales assistants A company … balancing tech investment with customer value The credibility to lead technically and influence at exec level Desirable but not essential: Strong AWS, containerisation and MLOps knowledge Confidence engaging directly with customers and enterprise stakeholders Hybrid role - minimum once per week onsite in Brighton.If you want to sit at the heart ...

underpin agentic workflows Own the end-to-end ML lifecycle from raw data and experimentation through to production deployment and continuous evaluation Lead MLOps infrastructure on AWS , building robust pipelines for training, monitoring, and retraining Bridge technical AI work with business strategy you'll have a seat at the table … solid TypeScript/API skills Hands-on experience with LLMs prompt engineering, evaluation, RAG architectures, safety considerations Cloud-native development on AWS and practical MLOps: CI/CD for models, version control, observability, retraining pipelines Familiarity with LangChain, Terraform, and modern AI tooling (Cursor, Gemini) is a strong plus Experience ...

platforms (Power BI, Qlik), managing semantic models, performance tuning, and automated refresh processes Support ML/AI initiatives by developing feature pipelines, enabling MLOps, and driving model deployment with Azure AI/ML/OpenAI Establish and maintain data quality, lineage, governance, and GDPR compliance across all data assets Lead … OpenAI, with knowledge of real-time data streaming technologies such as Event Hub and Kafka Proven capability in enterprise BI environments (Power BI, Qlik), MLOps practices, and Azure cloud architecture design Demonstrated team leadership skills, with relevant certifications such as DP-203 or Fabric Analytics Engineer Please get in touch ...

doing Develop and implement machine learning models and pipelines Work with structured and unstructured data at scale Deploy models into secure production environments Support MLOps practices including CI/CD for ML systems Optimise models for performance, accuracy, and reliability Work closely with stakeholders to translate requirements into technical solutions … deployment Experience with Python and ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn) Familiarity with data pipelines and cloud or on-prem environments Understanding of MLOps principles Ability to work in secure or regulated environments Eligibility Must be eligible for DV Security Clearance (5+ years UK residency required) Package ...

resource plans, timelines, and risk frameworks 🏗 Design AI Architectures Translate requirements into scalable AI/ML solutions Design architectures covering: Model development Data pipelines MLOps and monitoring Cloud integration (Azure, AWS, or GCP) Validate feasibility with engineering and delivery teams ✍️ Lead Tender & Bid Responses Own technical sections of AI RFPs … capability in scoping AI/ML programmes and estimating effort Deep understanding of: Machine learning (supervised & unsupervised) Generative AI & LLMs Embeddings, vector databases, RAG MLOps and model lifecycle management Experience with platforms such as: Azure ML, AWS SageMaker, Google Vertex AI Databricks, LangChain, Hugging Face Ability to develop architecture artefacts ...

models Work as part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build and maintain robust MLOps pipelines to support scalable, reproducible, and automated model development, deployment, and monitoring Leverage tools such as Airflow for workflow orchestration and MLflow for experiment tracking … skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for gaining insight into real-world datasets and clearly communicating through data visualization ...

preprocessing, augmentation, and validation workflows. Run structured experiments, evaluate model performance, and iterate based on measurable results Build, deploy, and operate end-to-end MLOps pipelines, including experiment tracking, model versioning, and production monitoring. Package and deploy models using Docker and cloud infrastructure, with a focus on reliability and scalability … familiarity with the Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar). Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred) Practical experience ...

emerging AI technologies and assess relevance to operational use cases. Drive continuous improvement of AI engineering practices, tooling, and delivery methods. Champion adoption of MLOps practices to enhance repeatability, traceability, and scalability. Promote knowledge sharing and best practice dissemination across engineering teams. Who we are looking for: The successful candidate … scalable ML architectures, including lifecycle management, monitoring, and resilience strategies Experience overseeing deployment using containerisation and orchestration platforms and governing CI/CD and MLOps practices Strong understanding of API-led integration within enterprise systems Experience embedding responsible AI principles into architectural design Strong understanding of secure coding, data protection ...

clear service boundaries Define enterprise-wide AI architecture guidelines, reusable components, and long-term roadmap to ensure consistency and acceleration of AI initiatives Implement MLOps/LLMOps pipelines for versioning, CI/CD, approvals, and controlled promotion across environments; enforce reproducibility Work closely with product owners, data scientists, engineers, security … Deep understanding of LLMs, generative AI, RAG patterns, vector databases, embeddings, and prompt/guardrail engineering Desirable Skills/Knowledge/Experience Knowledge of MLOps/AgentOps, CI/CD, and observability Strong understanding of regulated financial services environments Proven experience implementing AI risk controls, model governance, and auditability Ensure ...

clear service boundaries. Define enterprise-wide AI architecture guidelines, reusable components, and long-term roadmap to ensure consistency and acceleration of AI initiatives. Implement MLOps/LLMOps pipelines for versioning, CI/CD, approvals, and controlled promotion across environments; enforce reproducibility. Work closely with product owners, data scientists, engineers, security … Deep understanding of LLMs, generative AI, RAG patterns, vector databases, embeddings, and prompt/guardrail engineering. Desirable skills/knowledge/experience: Knowledge of MLOps/AgentOps, CI/CD, and observability. Strong understanding of regulated financial services environments. Proven experience implementing AI risk controls, model governance, and auditability. Ensure ...

dependencies to support executive decision-making. * Provide technical guidance across the AI landscape including generative AI, agentic systems, retrieval-augmented generation, fine-tuning, MLOps, and on-premise/cloud-native ML platforms, ensuring recommendations are grounded in implementation reality. * Collaborate with the client's internal teams (programme management, data engineering … complex, regulated, or high-security environments. * Deep technical fluency across modern AI/ML stacks: on-premise and cloud platforms (AWS, Azure, GCP), MLOps tooling, LLM orchestration frameworks, data engineering pipelines, and AI governance. * Exceptional ability to translate technical complexity into strategic narratives for non-technical senior stakeholders. * Strong commercial ...

Job Title Senior Data Scientist - CRM Location London – hybrid working (2/3 days in City offices) Salary To c£75,000 negotiable DoE Job Reference J13015 POSITION OVERVIEW We are super excited to be ...

architecture to ensure reliability, scalability, cost-efficiency, and security. Build platform capabilities such as: Prompt versioning Evaluation dashboards Real-time user feedback systems Promote MLOps best practices and responsible AI by establishing robust monitoring, guardrails, and launch protocols. Mentor team members and contribute to a culture of engineering excellence through … etc.) or database internals. Proven track record of delivering end-to-end projects and mentoring engineers. Direct experience with ML platforms and MLOps is required. ...

transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low-latency, highly reliable cloud … strong hands-on use of ML/DL frameworks (e.g., PyTorch, TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure-as-code practices. Proven technical leadership experience including ...

C#/.NET services. Performance & Scalability : Optimize GPU/CPU utilization, batching strategies, and memory management. Plan for multi-model and multi-tenant scenarios. MLOps & Lifecycle Management : Implement model versioning, artifact registries, and deployment workflows. Set up monitoring, logging, and alerting for solver performance. Security & Compliance : Apply best practices … performance profiling. Architecture : Proven experience designing scalable ML systems for production. APIs : Proficiency in gRPC/Protobuf and REST for cross-language integration. MLOps : CI/CD pipelines, containerization (Docker/Kubernetes), model registries, reproducibility. Performance Optimization : GPU acceleration (CUDA/cuDNN), mixed precision, XLA, profiling. Observability : Metrics, tracing, structured ...

needed for this role: Expert AI/ML Skills Strong in both traditional ML and modern LLM/RAG/agentic workflows Production Deployment & MLOps Comfortable shipping scalable AI systems using APIs, microservices, Docker/Kubernetes, and cloud (GCP ideal) Business Partnering Able to translate business needs into clear technical … LlamaIndex, etc.) Proven track record of deploying AI applications into production environments Strong understanding of API development, microservices, and containerization (Docker, Kubernetes) Knowledge of MLOps best practices Excellent problem-solving skills and ability to work in a fast-paced environment So, whats in it for you? Bonus Schemes A bonus ...

needed for this role: Expert AI/ML Skills – Strong in both traditional ML and modern LLM/RAG/agentic workflows Production Deployment & MLOps – Comfortable shipping scalable AI systems using APIs, microservices, Docker/Kubernetes, and cloud (GCP ideal) Business Partnering – Able to translate business needs into clear technical … LlamaIndex, etc.) Proven track record of deploying AI applications into production environments Strong understanding of API development, microservices, and containerization (Docker, Kubernetes) Knowledge of MLOps best practices Excellent problem-solving skills and ability to work in a fast-paced environment So, what’s in it for you? Bonus Schemes ...