26 to 50 of 55 MLOps Jobs in the City of London

their Databricks practice and needs multiple specialists to join this high-impact initiative. 🎯 DATABRICKS TEAM ROLES: Senior Data Engineering Consultant - Databricks/Snowflake focus Senior ML Engineer - Databricks specialisation (MLOps) Senior Platform Engineer - Databricks deployment expert Senior Databricks ML Engineer - Premium specialist role 🏢 Join a Dedicated Databricks Centre of Excellence: You'll be part of a specialist Databricks team delivering More ❯

their Databricks practice and needs multiple specialists to join this high-impact initiative. 🎯 DATABRICKS TEAM ROLES: Senior Data Engineering Consultant - Databricks/Snowflake focus Senior ML Engineer - Databricks specialisation (MLOps) Senior Platform Engineer - Databricks deployment expert Senior Databricks ML Engineer - Premium specialist role 🏢 Join a Dedicated Databricks Centre of Excellence: You'll be part of a specialist Databricks team delivering More ❯

engineering, optimisation). Excellent communication and stakeholder management abilities. A track record of managing teams and shaping development roadmaps. experience with cloud environments (AWS, Azure, GCP), and familiarity with MLOps lifecycle or solution architecture. More ❯

systems, data pipelines, and ETL processes Familiarity with cloud platforms, particularly Microsoft Azure Understanding of microservices architecture and distributed systems Experience with DevOps practices for AI/ML workflows (MLOps) Strong programming skills in Python and related data science libraries Demonstrated ability to work within solution architecture frameworks Preferred Qualifications Experience with multiple cloud providers beyond Azure Familiarity with container More ❯

systems, data pipelines, and ETL processes Familiarity with cloud platforms, particularly Microsoft Azure Understanding of microservices architecture and distributed systems Experience with DevOps practices for AI/ML workflows (MLOps) Strong programming skills in Python and related data science libraries Demonstrated ability to work within solution architecture frameworks Preferred Qualifications Experience with multiple cloud providers beyond Azure Familiarity with container More ❯

deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to validate impact Act as a technical lead within project teams, mentoring mid-level More ❯

deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to validate impact Act as a technical lead within project teams, mentoring mid-level More ❯

deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to validate impact Act as a technical lead within project teams, mentoring mid-level More ❯

with internal policies and external regulations. Provide technical input on risk mitigation strategies and onboarding documentation. Security & DevSecOps Integration Integrate AI security controls into CI/CD pipelines and MLOps workflows. Use tools such as Azure Key Vault, Microsoft Entra ID, and GitHub Actions for secure deployment and access management. Monitor AI systems using Azure Monitor, Log Analytics, and Application More ❯

SQL, data modelling, and modern data warehouse architecture Familiarity with data orchestration, workflow management, and CI/CD practices Experience in deploying and maintaining scalable data pipelines Exposure to MLOps practices and working with data science teams Familiarity with tools like MLflow or other model tracking/versioning tools Understanding of feature stores and data pipelines for ML/recommendation More ❯

SQL, data modelling, and modern data warehouse architecture Familiarity with data orchestration, workflow management, and CI/CD practices Experience in deploying and maintaining scalable data pipelines Exposure to MLOps practices and working with data science teams Familiarity with tools like MLflow or other model tracking/versioning tools Understanding of feature stores and data pipelines for ML/recommendation More ❯

in cloud platforms such as Google Cloud. Expertise in statistical techniques such as GLMs, classification, survival models, forecasting, and optimisation. Hands-on experience with experimentation and causal inference. Strong MLOps knowledge and experience deploying models into production environments using CI/CD. Experience with data visualisation tools like Tableau, and communicating to both technical and non-technical audiences. If this More ❯

model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO. Proficiency with CUDA programming and optimizing code for GPU acceleration. Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker. Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity environment. Experience contributing More ❯

and deploying object detection models, particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity More ❯

model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO. Proficiency with CUDA programming and optimizing code for GPU acceleration. Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker. Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity environment. Experience contributing More ❯

and deploying object detection models, particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity More ❯

rapidly evolving AI tools and actively incorporate them into solution design Requirements Strong background in data science and machine learning with solid understanding of statistics and programming Exposure to MLOps and experience deploying models into production environments Interest and practical experience in using emerging AI technologies such as co pilots, agentic frameworks, and generative AI applications Proven ability to manage More ❯

rapidly evolving AI tools and actively incorporate them into solution design Requirements Strong background in data science and machine learning with solid understanding of statistics and programming Exposure to MLOps and experience deploying models into production environments Interest and practical experience in using emerging AI technologies such as co pilots, agentic frameworks, and generative AI applications Proven ability to manage More ❯

ready. Key Responsibilities Build machine learning models for forecasting, propensity scoring, and segmentation Own workflows from data wrangling and feature engineering through to deployment and monitoring Operationalise models using MLOps tools in a cloud-native environment Architect datasets by merging structured and semi-structured data Work closely with engineers, product managers, and clients to align models with business needs Present More ❯

we looking for? Good experience working with Python & SQL Domain knowledge in customer & marketing - LTV, churn, segmentation, etc. Ability to build machine learning models in Python Production & deployment skills, MLOps Candidates must be based in the UK. Unfortunately we cannot offer sponsorship for this hire. Interested? Apply More ❯

leads to ensure consistency and quality Eligible for UK Government Security Clearance (SC minimum, DV preferred) Desirable Experience in client-facing roles or consulting Familiarity with LLMs, AI agents, MLOps or containerised deployments in classified settings Understanding of AI governance, ISO 42001, or model assurance frameworks More ❯

leads to ensure consistency and quality Eligible for UK Government Security Clearance (SC minimum, DV preferred) Desirable Experience in client-facing roles or consulting Familiarity with LLMs, AI agents, MLOps or containerised deployments in classified settings Understanding of AI governance, ISO 42001, or model assurance frameworks More ❯

prompt practices. Proven change leadership: you have driven ≥50% adoption with training and comms. Governance mindset: you have designed guardrails that pass risk and legal review. Working grasp of MLOps/GenAIOps (CI/CD, model registry, data lineage, evaluation). Clear communicator: you can brief boards and coach non-technical teams. Comfortable in a matrix: you align marketing, data More ❯

prompt practices. Proven change leadership: you have driven ≥50% adoption with training and comms. Governance mindset: you have designed guardrails that pass risk and legal review. Working grasp of MLOps/GenAIOps (CI/CD, model registry, data lineage, evaluation). Clear communicator: you can brief boards and coach non-technical teams. Comfortable in a matrix: you align marketing, data More ❯

Learning (Azure ML), covering training, testing, and deployment to production. * Select appropriate ML techniques (e.g., classification, regression, ensemble methods, survival models) to improve predictions and automate core processes. 2. MLOps & Model Lifecycle Management * Own the end-to-end ML lifecycle using Azure ML pipelines, Data Factory (ADF), and ML tracking tools. * Implement CI/CD pipelines with Azure DevOps, ensuring … Training & Innovation * Clearly communicate ML model behaviour, performance, and limitations to both technical and non-technical stakeholders. * Support and upskill colleagues in the use of Azure ML tools and MLOps practices. * Explore and propose innovations based on emerging trends in Azure AI/ML and financial analytics. Essential Criteria * Demonstrated experience deploying and managing production machine learning models using Azure … Machine Learning. * Strong grasp of MLOps principles, including CI/CD, model monitoring, and retraining pipelines. * Experience with Python, SQL, and Azure data services such as Data Factory, Blob Storage, or Data Lake. * Proficiency with DevOps tools (e.g., Git, Azure DevOps) and version control workflows. * Familiarity with reporting and visualisation tools (e.g., Power BI). * Strong communication skills, with the More ❯