76 to 100 of 603 MLOps Jobs in England

Data Mesh or Lakehouse architectures. Familiarity with Kubernetes, Docker, and real-time streaming technologies (e.g. Kafka, Kinesis). Exposure to ML engineering pipelines or MLOps frameworks. The Zego ways of working Teams work better with time to collaborate and space to get things done. We call it Zego Hybrid: some ...

Data Mesh or Lakehouse architectures. Familiarity with Kubernetes, Docker, and real-time streaming technologies (e.g. Kafka, Kinesis). Exposure to ML engineering pipelines or MLOps frameworks. Pay Transparency At Zego, we are committed to pay transparency and equal pay practices. In compliance with EU pay transparency regulations, we proactively disclose ...

documenting and defending architectural decisions and engaging in thoughtful technical debate. Not required, but it’s a plus if you also have: Experience with MLOps/LLMOps frameworks and best practices A PhD in Computer Science, Electrical Engineering or a related field. A background or work experience in life‐sciences ...

scalable enterprise workloads, integrating with clients' incumbent technology estates. Implement hybrid‐cloud and multi‐cloud strategies using modern data infrastructure (Kafka, Spark, data lakes), MLOps practices, and deployment platforms. Ensure compliance with data privacy regulations (including UK GDPR) and responsible AI standards, incorporating governance, observability, and security controls into ...

experience with RAG architectures, Agentic AI frameworks, and orchestration tools such as LangChain, LangGraph, AutoGen, and CrewAI. Proven experience applying Agile delivery, DevOps, MLOps, and LLMOps practices to enterprise AI programmes. Strong cloud architecture experience across Azure, AWS, or GCP. Experience in model deployment, monitoring, observability, governance, versioning, and operational ...

data science solutions. Ensure sharing best practices and learnings with other squad members. Design and spearhead the development of Gen AI, AI Agents and MLOps platforms, applications, and solutions driven by GenAI, deep learning and machine learning to address business challenges and elevate product performance. Build standards and recommendations ...

data science solutions. Ensure sharing best practices and learnings with other squad members. Design and spearhead the development of Gen AI, AI Agents and MLOps platforms, applications, and solutions driven by GenAI, deep learning and machine learning to address business challenges and elevate product performance. Build standards and recommendations ...

data science solutions. Ensure sharing best practices and learnings with other squad members. Design and spearhead the development of Gen AI, AI Agents and MLOps platforms, applications, and solutions driven by GenAI, deep learning and machine learning to address business challenges and elevate product performance. Build standards and recommendations ...

machine learning, and generative AI technologies to deliver innovative business solutions. Continuously improve platform performance, scalability, and operational efficiency while supporting AI governance and MLOps best practices. Unfortunately we are unable to progress with candidates that require sponsorship at this time Skills we would love you to have Experience working ...

calling patterns.Containerisation and orchestration for AI workloads at scale (Docker, AKS).Vector search at scale (Azure AI Search, Cosmos DB vector search).LLMOps and MLOps tooling and automated evaluation harnesses.Data privacy, security and compliance for AI systems, including responsible AI standards and GDPR considerations.Delivery in regulated and high-governance environments.We ...

data pipelines and ML systems based on established patterns. Contribute to platform capabilities that support data transformation (DBT), pipeline orchestration (Airflow/Astronomer), MLOps workflows including model versioning and deployment automation and much more Support platform users including data engineers, ML engineers, data scientists, and analysts by troubleshooting issues, providing ...

expertise on AWS, especially Amazon Bedrock and Bedrock AgentCore, alongside SageMaker, Lambda and Step Functions, with CDK or equivalent IaC. Hands-on LLMOps and MLOps experience, including agent and trajectory evaluation, tracing (e.g. OpenTelemetry), guardrails, cost monitoring and automated model pipelines. A clear understanding of agent security risks, such ...

frameworks. Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Databricks, or equivalent cloud platforms. Data visualisation and storytelling tools such as Power BI. MLOps and model lifecycle management. Preferred Qualifications Experience in client-facing consulting roles. Exposure to cloud-based AI and analytics platforms. Understanding of Responsible AI and governance ...

behaviours. Write production-quality Python and SQL, and work with engineers to integrate successful solutions into scalable AWS services, data pipelines, and APIs. Apply MLOps and LLMOps practices, including version control, automated tests, CI/CD, reproducible deployment, monitoring, drift detection, and rollback. Define and maintain offline and live evaluation ...

domains. Ability to lead architectural discussions and technical trade‐offs without losing sight of the details. Familiarity with cloud infrastructure (AWS preferred) and modern MLOps practices. Commitment to people development: mentoring, performance conversations, and building high‐performing teams. Bonus: experience with NLP on financial contracts, RAG or LLM‐based applications ...

across fulfilment ranking, model delivery, offline and online evaluation, low-latency services, observability and product quality. Its published work includes shared model-serving and MLOps paths, automated evaluation and retraining, caching and telemetry, and agent-assisted release and operational workflows. What is the role? We are looking for a Senior ...

behaviours. Write production-quality Python and SQL, and work with engineers to integrate successful solutions into scalable AWS services, data pipelines, and APIs. Apply MLOps and LLMOps practices, including version control, automated tests, CI/CD, reproducible deployment, monitoring, drift detection, and rollback. Define and maintain offline and live evaluation ...

services such as Azure OpenAI, AI Foundry or AI Search, with Docker and Kubernetes Understanding of schema validation frameworks (e.g., JSON Schema, Pydantic) and MLOps tools such as MLflow or Airflow Strong communication ability to explain trade-offs around cost, latency and accuracy to technical and non-technical audiences Nice ...

maintain real-time AI pipelines using WebSockets and SSE , ensuring seamless low-latency delivery for voice (ASR/TTS) and text applications. Architecture & MLOps: Deploy and orchestrate models within containerized microservice architectures ( Docker/Kubernetes ), ensuring robust monitoring, security, and scalability. Collaborative Delivery: Work closely with Business Analysts and internal ...

design principles. Technical Stack Core: Power BI SQL Server Tool-agnostic architecture patterns Cloud platform comparison (Azure, AWS, GCP), API design Microsoft Fabric MLOps frameworks What You'll Bring Professional experience spanning multiple areas of data and AI (analytics, engineering, or data science). Strong understanding of the complete data ...

with measurable impact, including deploying or working alongside ML/AI systems in production Bonus: Trust & Safety, Content Moderation, or Integrity engineering experience MLOps experience: deployment, monitoring, and versioning of ML models Experience with SQL, data analysis tools, real‐time streaming systems (Kafka, Redis), or event‐driven architectures Familiarity with ...

knowledge in the following: Python AWS Kubernetes Spark & distributed computing dbt Terraform Data Warehousing (we use Databricks but experience with other platforms is fine) MLOps implementation (desirable but not required) Airflow (or other orchestration tooling) Governance Things to note Just to let you know, we are dog friendly company ...

along with data extraction, manipulation and feature engineering techniques Experience with Spark, agile delivery methods and CI/CD practices Familiarity with DevOps and MLOps tools and practices, such as Docker, Terraform and MLFlow Confidence influencing and communicating with stakeholders across technical and non-technical teams Ideally, exposure to cloud ...

Learning Applied machine learning, computer vision, object detection, image classification, model development and evaluation, data annotation and curation, training pipelines, performance optimisation, edge ML, MLOps, deployment and maintenance of ML solutions, Python development, Python‐based ML frameworks, PyTorch, TensorFlow, sklearn, OpenCV, NumPy, feature development, code review, pytest, linting, bug fixing ...

optimize visualization performance Enhance dash boarding capabilities to deliver fast and flexible experiences Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration. Build tools to automate retraining, monitoring, and deployment ...