151 to 175 of 219 MLOps Jobs in the UK excluding London

commercial deployment, focusing on performance, reliability, and maintainability. Key qualifications include expertise in TensorFlow and Python, experience in API development, and familiarity with MLOps practices. Joining means working on cutting-edge ML solutions and collaborating with experts across various fields. #J-18808-Ljbffr ...

CODAS project and related initiatives at AND-E Lab. Ideal candidates have 5+ years in ML/AI, strong Python, cloud/MLOps experience, and a collaborative mindset to work with partners and stakeholders across experiments and #J-18808-Ljbffr ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

cases (forecasting, ATP optimisation, document AI, anomaly detection). Define ML data contracts and embed models in operational processes (Fiori, SAC). Establish MLOps foundations: pipelines, CI/CD, monitoring, retraining, drift. Chair the Data & AI Design Authority, driving alignment across internal teams and multiple SI/vendor partners. Govern ...

integration between connected devices, cloud services, data platforms, and engineering teams. As the capability matures, the role will provide a clear development path into MLOps and ML platform engineering, supporting model deployment, model lifecycle controls, ML pipeline automation, and governed promotion of machine learning solutions from development into production. … validation, monitoring, transformation and handover between operational platforms and analytical environments. Proactively identify opportunities to simplify, automate and strengthen digital platform delivery. Growth into MLOps and ML platform engineering Develop capability in MLOps practices such as experiment tracking, model packaging, model registry, model promotion and governed deployment workflows. Support ...

Machine Learning and Generative AI solutions in production environments. Work with modern AI frameworks, LLMs, RAG, prompt engineering and vector databases. Ensure robust MLOps practices, APIs, data pipelines and modern software engineering disciplines are in place. Strategic & Stakeholder Engagement Act as a thought leader, willing to challenge the business … Machine Learning and Azure Data Platform technologies. Knowledge of LLMs, RAG, prompt engineering, vector databases and modern AI frameworks. Experience with APIs, data pipelines, MLOps practices and modern software engineering disciplines. Experience managing partner-led delivery and a mix of onshore/offshore teams. Microsoft certifications (e.g., Azure AI Engineer ...

goals, and ensure architectural integrity and commercial viability. The role requires deep knowledge of Data Lakehouses, Data Mesh, real-time analytics, and GenAI/MLOps, with a proven ability to scale #J-18808-Ljbffr ...

integrity, normalisation and scalability. Build, deploy, monitor and maintain ML Models. Key use cases include feed optimisation, recommendation algorithms, classification tasks, predictive analytics and MLOps deployments. Continuously evaluate the effectiveness of our models and feed logic, providing recommendations for architecture improvements and performance optimisation. What Youll Bring: Proven years … Python. Familiarity with data manipulation libraries (e.g. PySpark, Pandas, Numpy) and machine learning frameworks (e.g. scikit-learn, TensorFlow or PyTorch). Experience with MLOps tools (e.g., MLflow, Databricks Model Registry, Unity Catalog, Vertex AI) and version control (Git). Strong coding practices with experience in code optimisation, ETL frameworks ...

driven systems that perform reliably in production and drive conversion. You'll work alongside a multi-skilled group of data scientists, AI engineers and MLOps specialists in cross-functional teams. We deliver against quarterly OKRs, own our work end to end, and put collaboration at the heart … Solid grounding in statistics and ML theory across supervised and unsupervised learning, NLP (entities, intent), recommendation, prediction and uplift modelling Full model lifecycle and MLOps: containerisation (Docker/ECR) and deployment on AWS Working with large text datasets and data pipelines Nice to have: sales psychology applied in data products ...

Senior ML Ops Engineer London (Hybrid, 1-2 days per week) | £75,000 - £85,000 + 10% Bonus This is an opportunity to join a growing AI and data organisation that is using advanced analytics ...

production ML—owning problems end-to-end to accelerate model delivery. You’ll collaborate with the ML team to improve data quality, observability, and MLOps practices, while scaling infrastructure for faster iteration and reliability. #J-18808-Ljbffr ...

Personalize team in the UK. You will shape and own medium-sized ML features end-to-end, from framing to deployment, working with ML, MLOps and software engineering to deliver impactful personalization capabilities. The role emphasizes productionising models as APIs, real-time and batch processing, and ongoing research. ...

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 ...

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 ...

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 ...

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 ...

Analysis: Apply established data science and machine learning techniques to analyse data and solve business problems under the guidance of senior team members. Production & MLOps: Build, test, and help deploy machine learning models into production environments. Contribute to the design and maintenance of MLOps pipelines to ensure solutions are scalable ...

customers. They will be subject matter experts in the areas of Predicative AI, Machine Learning, Generative AI along with associated capabilities in areas like MLops, Data Pipelines, and DevOps. The role will interface directly with the customers' business, data science and IT Operations teams to establish CDW credibility and position … learning, lab time and formal training. What you will do Position CDW Custom AI capabilities - Engage with all Customer AI personas: technical personas (CDO, MLOps, AI/ML Engineer, Data Scientist), outcome-driven personas (CEO, CTO, LOB) and ITDMs (CIO, VP Infrastructure). Technical SME on CDW Custom AI – Maintain ...

customers. They will be subject matter experts in the areas of Predicative AI, Machine Learning, Generative AI along with associated capabilities in areas like MLops, Data Pipelines, and DevOps. The role will interface directly with the customers' business, data science and IT Operations teams to establish CDW credibility and position … learning, lab time and formal training. What you will do Position CDW Custom AI capabilities - Engage with all Customer AI personas: technical personas (CDO, MLOps, AI/ML Engineer, Data Scientist), outcome-driven personas (CEO, CTO, LOB) and ITDMs (CIO, VP Infrastructure). Technical SME on CDW Custom AI – Maintain ...

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 ...

implementation leadership for major features and platform initiatives, including writing and reviewing critical-path code where the work demands it. Define and oversee the MLOps strategy spanning model training, deployment, monitoring, and lifecycle management on Kubernetes across AWS, GCP, and Azure. Establish and evangelize engineering best practices across services, including … experience with Kubernetes and at least one major cloud provider (AWS, GCP, or Azure), with working familiarity across multi-cloud environments. Demonstrated experience with MLOps tooling and patterns, including model registries, experiment tracking, and CI/CD for. Proven ability to lead architectural strategy across multiple teams and services, balancing ...

We recognise our people are the best thing about Red Badger and that a truly diverse workplace where people are free to be themselves is essential for great culture and great outcomes. If you like ...

connected products and industrial IoT capabilities. Initially focus on DevOps, cloud operations, IoT data flows, deployment automation and environment management, with a path into MLOps and ML platform engineering as capability matures. #J-18808-Ljbffr ...