51 to 75 of 202 MLOps Jobs in the UK

understanding of data modelling (E) Programming skills in Python and/or Scala for data processing (D). Experience with machine learning pipelines or MLOps frameworks (D). Personal Attributes: Confident communicator able to engage both technical and non-technical audiences. Proactive, innovative, and committed to continuous improvement. Collaborative, with ...

Supporting the full ML lifecycle, from experimentation to deployment and optimisation. Applying best practices in data engineering and contributing to architectural decisions. Using modern MLOps tools and CI/CD approaches to improve reliability and efficiency. Contributing to a culture of knowledge-sharing and continuous improvement. Key Skills & Experience Strong ...

resolve incidents efficiently. Continuously improve ML Ops processes, tooling, and automation for efficiency and reliability. What Were Looking For Essential: 5+ years experience in MLOps, DevOps, or related roles. Strong knowledge of ML lifecycle management, deployment, monitoring, and model maintenance. Hands-on experience with Python (and ML frameworks), containerisation (Docker ...

frameworks, including embeddings, prompt engineering, or fine tuning Experience building end to end ML pipelines, including model validation, optimisation, deployment, and monitoring Understanding of MLOps practices, including model versioning, model registries, CI/CD for ML, and automated training/inference workflows Ability to translate business problems into analytical tasks ...

Radar, EDP, and upstream/downstream applications. Design cloud‐native solutions using AWS services and ensure high availability, observability, and security. Define architecture for MLOps, including CI/CD, deployment, monitoring, versioning, and governance. Collaborate with engineering, product, data science, and security teams to align architecture with business goals. Produce ...

technologies and data challenges. The other stuff we are looking for A passion for continuous improvement. Some experience in machine learning (BigQueryML), MLOps or Gen AI applications. Ability to foster a positive and engaging team culture. Experience working with big data. What's in it for you Our goal ...

driven solutions that create measurable business value such as revenue growth, efficiency improvements, or risk reduction Experience in insurance or consulting Experience with MLOps Experience with fine-tuning or adapting foundation models, such as LoRA Experience with WTW actuarial software What we offer Enjoy a benefits package designed to help ...

driven solutions that create measurable business value such as revenue growth, efficiency improvements, or risk reduction Experience in insurance or consulting Experience with MLOps Experience with fine-tuning or adapting foundation models, such as LoRA Experience with WTW actuarial software What we offer Enjoy a benefits package designed to help ...

diligence, post-acquisition value creation, or technology strategy - Experience with AWS AI services (Amazon Bedrock, SageMaker, Kiro) or equivalent cloud AI platforms - Experience with MLOps/AIDLC workflows for production AI systems including model deployment, monitoring, and governance - Track record leading large-scale technical events (hackathons, workshops) with ...

trade-offs between model quality, latency, throughput, and token efficiency - particularly within the cost and performance constraints of real-time financial workflows. - MLOps & AgentOps Strategy: Guide customers on CI/CD pipeline design, automated testing for non-deterministic outputs, model versioning, and observability (tracing, drift detection) - establishing patterns that satisfy ...

MLOps Engineer, you will play a pivotal role in designing, building, and operating the platforms, pipelines, and infrastructure that enable machine learning solutions to move reliably from experimentation to production. This is a blended role combining MLOps, Data Engineering, and DevOps, well-suited to an engineer who enjoys working across … environment management, and deployment using Terraform, ARM templates, or Ansible. Essential Technical Skills: Programming: Python, SQL, PySpark, Bash ML Frameworks: TensorFlow, PyTorch, Scikit-learn MLOps & Model Management: MLflow, Model versioning, CI/CD Cloud & Big Data: Databricks, Databricks APIs, MCP, Blob Storage Data Engineering: ETL/ELT pipelines, DLT, Delta ...

tools). * Experience in a contractor or project-based delivery model preferred. * Exposure to OT/SCADA environments or energy sector data. * Exposure to MLOps workflows or collaboration with data science teams. ...

product and systems thinking with a practical, impact-led mindset. Nice to Have AWS experience (e.g. SageMaker, Bedrock, Lambda, S3, Redshift). Familiarity with MLOps practices. Background in adtech, media, fraud, or adversarial systems. Why Join Work on technically challenging, high-scale AI problems. End-to-end ownership from experimentation ...

thinking DevSecOps Engineer to join our Defence client, offering a unique opportunity to work at the forefront of secure, scalable software delivery across DevSecOps, MLOps, and cloud technologies. In this role, you will help push the boundaries of what's possible-from securely updating deployed equipment to enabling resilient, high ...

should be comfortable designing data persistence layers using PG Vector, Pinecone, Milvus, or Mongo Atlas to handle large amounts of unstructured data. The MLOps Engineer: You don't just write code; you ship it. Our client requires experience deploying GenAI models into production using Kubernetes (or OpenShift) and establishing robust ...

testing, lineage and observability to ensure high-quality, trusted datasets. Support governance and privacy-conscious data handling. • Collaboration & Enablement (10%) : Partner with Data Science, MLOps, Product and commercial teams to deliver production-ready data solutions. Support and mentor others while communicating clearly with stakeholders. What You'll Love About This ...

engineers, business stakeholders) to define project scope, interpret model results, and clearly present data-driven recommendations to both technical and non-technical audiences. Deployment & MLOps: Collaborate with ML/Data Engineers to deploy, monitor, and maintain ML models in a production environment, ensuring stability and performance over time. Required Skills ...

strategies proactively Support documentation of architecture, pipelines, and operational processes Good to Have Exposure to AI/ML data workflows (feature engineering, model inputs, MLOps basics) Awareness of LLMs/Agentic AI architectures from a data platform perspective Experience with other platforms such as AWS, GCP, Snowflake, BigQuery, Redshift Familiarity ...

techniques. Experience applying advanced AI models, including computer vision and deep learning, to solve real‐world problems. Experience with AWS, Kubernetes, VertexAI, Labelbox, and MLOps practices. Experience with SQL and NoSQL databases (MongoDB, Elasticsearch, etc.). Experience with graph analysis and network science for fraud detection. Experience with automated data ...

architectural decisions that balance speed, quality, and regulatory compliance Also Valuable Experience with healthcare data interoperability (FHIR, HL7, DICOM) Exposure to ML model serving, MLOps pipelines, or ML frameworks (TensorFlow, PyTorch) Understanding of GDPR, HIPAA, or UK Data Protection Act compliance Experience with Infrastructure as Code (Terraform, CloudFormation ...

multi‐structured wealth data. AI Readiness: Implement strategies to make data "AI-ready," focusing on data quality, low-latency access, and the integration of MLOps principles into the data engineering workflow. Technical Governance: Set and enforce high standards for code quality, documentation, and testing. Drive the adoption of modern engineering ...

avoid duplication, ensure accountability. Collaborate with Product Managers to embed AI capabilities into broader product strategies. Work closely with Data Scientists, ML Engineers, and MLOps teams to ensure technical feasibility and scalability. Act as the primary liaison between business stakeholders and AI team. Educate stakeholders on AI capabilities, limitations ...

Synapse, BigQuery) Ensure robust data engineering practices (Airflow, dbt, Prefect) and governance (Collibra, Purview) Drive scalable lakehouse architectures (Delta Lake, Iceberg, Hudi) Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and CI/CD pipelines Ensure scalable deployments … across academia, startups, and hyperscalers Your Background Proven experience leading enterprise-scale AI transformation programmes Deep technical expertise across Python, .NET, cloud platforms, and MLOps Strong understanding of data governance, architecture, and DevSecOps Demonstrated ability to deliver measurable business outcomes and ROI Exceptional stakeholder management and executive communication skills Additional ...

training datasets, and inference pipelines 3. Model Development & Deployment Strategy Guide data scientists on: Model selection and evaluation strategies Experiment tracking and reproducibility Design MLOps frameworks for: CI/CD of ML models Model versioning and governance Monitoring drift, accuracy, and bias 4. Technology & Platform Governance Define standards for: Programming … recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps & Deployment Model lifecycle management CI/CD pipelines Containerization (Docker, Kubernetes desirable) Model packaging and REST APIs Cloud & Tools (Any combination) AWS/Azure/ ...

Location: Manchester Working: 3 days onsite (Tues-Thurs) Salary: £100k + extensive package (TC circa £150k) The Role Leading a team of Data, DataOps & MLOps Engineers within a global asset manager's European Data function. You'll drive delivery of scalable, cloud-based data solutions, supporting analytics, data science ...