26 to 41 of 41 MLOps Jobs in Central London

Python and SQL (BI tools such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers with attention to detail Have More ❯

Python and SQL (BI tools such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers with attention to detail Have 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 ❯

and deployment workflows Analytics & Reporting – enabling insights through dashboards, reporting tools, and data aggregation Automation – building scripts and utilities to streamline and optimize operations Data Engineering/DevOps/MLOps – contributing to data infrastructure, deployment pipelines, and scalable systems Must-Have Skills: Strong programming skills in Python with ability to write modular and maintainable code Solid understanding of data structures … or containerization (Docker) Awareness of analytics tools (e.g., Power BI, Tableau), dashboards, or reporting pipelines Experience with automation scripts, data wrangling, or internal tooling Basic understanding of DevOps or MLOps workflows and CI/CD pipelines Eligibility BE/B.Tech or equivalent –2025 pass-outs Academic background in CS/IT/ECE/EE/Math or other technical More ❯

plus Demonstrated experience building APIs to support analytics/research/actuarial functions in an insurance company setting Experience with cloud technologies like Snowflake and Databricks Familiarity with the MLOps framework Required Skills Exceptional collaboration and relationship building skills Comfortable handling ambiguous concepts and breaking down complex problems into manageable pieces Resilient problem solving and critical thinking skills Ability to 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 ❯

plus Demonstrated experience building APIs to support analytics/research/actuarial functions in an insurance company setting Experience with cloud technologies like Snowflake and Databricks Familiarity with the MLOps framework Exceptional collaboration and relationship building skills 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 ❯

excited by the challenge of applying data science at scale. You’ll work closely with cross-functional teams to operationalize models, support product development, and contribute to a modern MLOps pipeline. What You’ll Do Develop and deploy predictive models using behavioural and real-world data Translate complex datasets into actionable insights that improve healthcare outcomes Contribute to the full … and feature engineering to model deployment and monitoring Collaborate with engineering and product teams to ensure models are integrated into production systems via scalable pipelines Champion best practices in MLOps, including CI/CD for ML, model versioning, testing, and monitoring Design experiments (A/B testing, uplift modelling) to measure impact and optimize performance What We’re Looking For … behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data pipelines Excellent communication skills—able to More ❯

Our Company: QiH is a fast-growing, innovative, and progressive scale-up business headquartered in London with a collective of brilliant brains in Skopje. We are at the start of an exciting journey as we build out our internal engineering More ❯

extensive geospatial information. You will take ownership not only of modeling and metric development but also of the end-to-end ML lifecycle, including deployment and monitoring using modern MLOps frameworks. Collaboration with data engineers and cross-functional teams is essential, as you’ll help shape the ML strategy and drive innovation in how healthcare behaviors are understood and acted … Strong Python skills and experience with Databricks or similar platforms Proven track record in predictive modelling with messy, real-world datasets (survey, geospatial, or similar) Hands-on experience with MLOps tools and practices (e.g., MLFlow) and deploying models in cloud environments (GCP, AWS, or Azure) Proactive, creative problem solver with a startup mindset and strong communication skills Comfortable taking technical More ❯

API Gateways Guide distributed system architectures and internal service integration . Define best practices for service-to-service communication and data management . AI & ML Enablement Set vision for MLOps platforms and streamline machine learning workflows . Enable deployment of traditional and generative AI models into internal platforms. Developer Experience & DevOps Tooling Shape strategy for CI/CD , Infrastructure as … on internal tooling and shared services. Track record of delivering internal products that boost developer workflows , reliability , or deployment velocity . Hands-on experience with AI/ML platforms , MLOps , and deploying machine learning models into production environments. Core Focus Areas Core Platform Engineering Developer Experience (DevEx/DX) Engineering Productivity DevOps Tooling Observability Solutions Platform as a Service (PaaS More ❯

. API Development: Experience building data-centric APIs, especially with FastAPI on serverless platforms like Google App Engine . Streaming Data: Practical experience building real-time data pipelines. DevOps & MLOps: Knowledge of Infrastructure as Code (Terraform), MLOps principles, and containerization (Docker, Kubernetes). What They Offer Work that impacts elite football performance and club-wide success Access to real-world More ❯

Head of Data & AI London (Hybrid) Up to £130,000 A high-impact leadership opportunity at a fast-scaling, cloud-native financial services business. This is your chance to take full ownership of the data strategy - spanning engineering, analytics, governance More ❯

Machine Learning Engineer (SC Cleared) London (Hybrid) 2 Month Contract £550/day (Inside IR35) Machine Learning Engineer needed with active SC Security Clearance, plus strong Databricks, MLFlow and MLOps experience. The ideal candidate will have a strong background in Machine Learning (ML) Engineering and in-depth expertise in operationalising models in Databricks, MLFlow and MLOps environments. A chance to More ❯