426 to 450 of 604 MLOps Jobs in England

built, governed, and evaluated across the Global Public Sector team. You will define standards for responsible AI, model governance, and production MLOps used by multiple engineers and clients. You will architect high-risk AI systems, lead incident resolution related to model safety and data integrity, and coach senior engineers while ...

commercial outcomes with executive leadership. You will manage 100+ engineers across distributed pods, ensure platform modernization, and drive value with real-time analytics, MLOps, and GenAI integration. #J-18808-Ljbffr ...

engine for ranking, retrieval, and recommendations. You will define the ML strategy, build scalable systems, and mentor a high-performing team across machine learning, MLOps, and experimentation. You will drive multi-task models, graph-aware representations, and agentic AI approaches to improve user search, discovery, and itineraries at scale within ...

ingestion and feature engineering to production deployment and monitoring. The role focuses on building scalable, low-latency ML systems and establishing robust governance and MLOps practices. The successful candidate will lead design and implementation of end-to-end ML architectures, coach engineers, and ensure alignment with enterprise standards, while delivering ...

TokenHub and MCP ecosystem, working with enterprise customers and cross-functional teams. Required are 2+ years in Gen AI/LLMs, strong cloud and MLOps experience, and excellent English. Mandarin is a plus for collaboration with China HQ. This role focuses on architecture, delivery, and customer success across enterprise accounts. ...

senior technical voice for the most sensitive AI decisions our clients face. Your work will define standards for responsible AI, model governance, and production MLOps, architect high-risk systems, and build reusable capabilities that enable multiple teams to ship safer AI at scale. #J-18808-Ljbffr ...

Learning Engineer to translate research into robust, production‐ready ML services within a privacy‐sensitive, multi‐partner environment. You will set ML engineering and MLOps direction for CODAS workstreams and lead how research gets built, tested, and shipped. Oxford hybrid is preferred, though we’d consider fully remote ...

complex domain-specific problems. You will explore cutting-edge architectures and rapidly translate theoretical breakthroughs from arXiv into functional, high-performance prototypes. Collaborating with MLOps, you will implement data strategies, run rigorous experiments, optimise compute and memory usage, and ensure smooth hand-off into scaled production. #J-18808-Ljbffr ...

Evaluate and apply emerging ML and deep learning techniques Key Skills Required: Machine Learning/Deep Learning Recommendation & Personalisation Systems Data Pipelines & Feature Engineering MLOps & Production Deployment A/B Testing & Experimentation Python/ML Frameworks Large-scale Structured & Unstructured Data To be Considered: Please either apply by clicking online ...

Evaluate and apply emerging ML and deep learning techniques Key Skills Required: Machine Learning/Deep Learning Recommendation & Personalisation Systems Data Pipelines & Feature Engineering MLOps & Production Deployment A/B Testing & Experimentation Python/ML Frameworks Large-scale Structured & Unstructured Data To be Considered: Please either apply by clicking online ...

technology to find innovative and new ways of working. You should be able to demonstrate: Significant experience working as a System Administrator, HPC Engineer, MLOps Engineer or equivalent technical role Modern GPU server deployment, tuning and management Advanced networking technologies (Infiniband, RDMA, RoCE) Advanced Linux skills and experience working with ...

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 ...

Senior MLOps Engineer London (Hybrid) | £75,000 - £85,000 + Bonus + BenefitsThis is an opportunity to take ownership of the infrastructure powering a growing AI platform. You'll work across machine learning, NLP, and emerging AI technologies, helping build scalable systems that support real-world impact. The Company … making and deliver better outcomes. They are investing heavily in their AI platform and expanding their engineering capability. The Role Own and develop the MLOps infrastructure supporting AI services. Build and maintain orchestration pipelines using Dagster, Airflow, or Prefect. Deploy and manage ML workloads on Kubernetes and cloud platforms. Implement ...

Software Engineers, and Product teams to deliver scalable solutions Contribute to the development of greenfield machine learning products and capabilities Drive best practices across MLOps, monitoring, observability, and model lifecycle management Your Skills & Experience Strong commercial experience within Machine Learning Engineering, Data Science, or MLOps Experience deploying, monitoring, and maintaining ...

that feed our dispute systems. Collaborate with platform and backend engineers to integrate models seamlessly. Experience and qualifications 5+ years of experience as an MLOps/ML Engineer. High proficiency in writing clear, production‐ready Python code. Experience with production ML models (online or offline) and standard MLOps practices. Experience ...

delivery of enterprise-scale AI/ML and Generative AI solutions. The role requires deep expertise in LLMs, Agentic AI, NLP, RAG architectures, MLOps, and cloud-native AI platforms on Google Cloud Platform (GCP). The architect will be responsible for defining AI solution strategies, driving technical direction, establishing architecture … Engineering AI Agents and Multi-Agent Systems Copilot and Conversational AI development BigQuery Dataflow Cloud Functions GKE Pub/Sub IAM and Security Controls MLOps/LLMOps CI/CD for ML Version Control Automated Evaluation Monitoring & Observability Rollback Frameworks Microservices API-driven Integration Distributed Systems Required Experience 14+ years ...

hallucination and model risk Supporting the move towards increasingly high‐risk and high‐complexity AI/ML use cases Establishing best practice across MLOps, CI/CD and deployment Influencing senior engineers and technical stakeholders without direct line management Helping engineering teams use AI‐assisted development tools effectively within their … Learning/AI engineering AWS Agentic AI and LLM‐based applications Retrieval Augmented Generation (RAG) LangChain and/or LangGraph Vector databases and retrieval MLOps and production deployment AI evaluation, testing and observability AI governance, model risk and engineering controls ML frameworks such as PyTorch, TensorFlow or Scikit‐learn Experience ...

Experience fine‐tuning LLMs (e.g., LoRA, QLoRA, RLHF) specifically for domain‐specific enterprise applications. Taken responsibility of models from concept to production, utilising strong MLOps and LLMOps practices to ensure scalable, reliable, and monitorable deployments. High proficiency in Python and modern software development practices, including rigorous testing, code reviews … Computer Science, Artificial Intelligence, Statistics, Data Science, or a related quantitative field. Experience working with scalable cloud infrastructure (AWS, GCP, or Azure) and MLOps tools for model training, monitoring, and deployment. Background in forecasting, planning, or analytics applications. Familiarity with Anaplan or similar enterprise planning platforms. Experience with A/ ...

/B tests, owning statistical validity and turning results into recommendations teams can act on Collaborate with Engineers to ship models via reproducible MLOps workflows: experiment tracking, model serving, alerting, and production monitoring Communicate model choices, limitations, and trade-offs clearly to both engineers and non-technical stakeholders 3+ years … comfortable with large transactional datasets and common DS/ML libraries (e.g. pandas, scikit-learn, XGBoost, PyTorch or similar) Experience collaborating on MLOps-style workflows (experiment tracking, serving, monitoring) and shipping with engineers Able to communicate uncertainty and model limitations clearly to technical and non-technical audiences Bachelor ...

deliver end-to-end data pipelines. Optimise performance, reliability, and cost-efficiency across all data workflows and systems. Lead development of Superscript’s MLOps capabilities, ensuring seamless model deployment, monitoring, and feedback loops. Own and improve data quality frameworks and observability to ensure trust in business-critical data assets. Produce … frameworks, version control (Git), and containerisation (Docker/Kubernetes). Strong background in data modelling, warehousing, and supporting analytical and ML workloads. Exposure to MLOps tools including MLFlow, kedro and Amazon Sagemaker. Development and maintenance of real time products like APIs using FastAPI/Flask. Operates autonomously with strong ownership ...

deployment. Drive innovation in machine learning algorithms, neural networks, and emerging AI technologies including generative AI and multi‐modal systems. Oversee the implementation of MLOps pipelines, model monitoring, and automated deployment systems. Team Leadership & Mentorship: Lead and mentor a team of AI engineers, data scientists, and data engineers. Foster … Excellence: Proven experience building production‐scale AI systems with focus on performance, reliability, and maintainability. Expertise in software architecture, distributed systems, and DevOps/MLOps practices. Leadership & Collaboration: Demonstrated ability to lead technical teams, drive consensus on technical decisions, and collaborate effectively across departments. Experience mentoring engineers and fostering technical ...

/B tests, owning statistical validity and turning results into recommendations teams can act on Collaborate with Engineers to ship models via reproducible MLOps workflows: experiment tracking, model serving, alerting, and production monitoring Communicate model choices, limitations, and trade‐offs clearly to both engineers and non‐technical stakeholders What … comfortable with large transactional datasets and common DS/ML libraries (e.g. pandas, scikit‐learn, XGBoost, PyTorch or similar) Experience collaborating on MLOps‐style workflows (experiment tracking, serving, monitoring) and shipping with engineers Able to communicate uncertainty and model limitations clearly to technical and non‐technical audiences Bachelor ...

Advanced Python development skills. Experience building scalable AI services and APIs. Strong backend development and integration experience. Knowledge of software engineering best practices and MLOps workflows. Experience with Microsoft Azure (preferred), AWS, or Google Cloud Platform. Experience designing microservices-based and distributed architectures. Expertise in experiment design and scientific evaluation … Electrical & Electronic Engineering Related STEM discipline Computer Vision and image understanding systems. AI agent frameworks and autonomous workflows. Knowledge graphs and semantic retrieval systems. MLOps and model deployment pipelines. Team leadership or technical management experience. Additional Information We bring together entrepreneurial, tech-driven people to deliver innovative solutions for leading ...

hybrid SQL/Python architecture (dbt, Snowflake) to extract rich, localized temporal signals from high-volume transactional retail data. End-to-End Deployment (MLOps): Partner with our engineers to transition your models from prototype into scalable, monitored, and reliable production pipelines using tools like MLflow and Optuna. Your Skills Strong … transformation tools like dbt. Cloud & Data Infrastructure: Experience working with scalable cloud infrastructure (AWS, GCP, or Azure), and handling columnar data formats like Parquet. MLOps Exposure: Experience with tools and frameworks for training, tracking, deploying, and monitoring models in production (e.g., MLflow, Optuna, Prefect, or Airflow). Background in supply ...

part of the Data and AI platform team; you’ll get to pioneer on real world problems, bringing your knowledge of AI/ML, MLOps and LLMs to bear - collaborating cross team to make your vision a reality. You’ll be backed by our platform team, and have a wealth … scientific evaluation with the operational maturity to champion high-value applications and confidently push back on unsuitable AI use cases. Design, refine and build MLOps component of the data and AI platform, from Vector Databases through feature stored and model serving, all at the millisecond scale. Implement CI/ ...