51 to 75 of 220 MLOps Jobs in the UK excluding London

datasets (scientific, biomedical, or enterprise data) Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef) Exposure to production ML systems and MLOps practices Familiarity with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn, or similar) to communicate insights effectively Experience with human ...

data‐driven systems in production or near‐production settings. Experience with generative AI systems, LLM‐enabled applications or evaluation pipelines. Experience with cloud platforms, MLOps tooling, model serving or platform engineering. Advanced use of Linux, Docker, version control, CI/CD and service‐oriented deployment practices. Experience working across ...

infrastructure for latency, scalability, and cost. Build infrastructure to monitor model performance, data drift, and other key metrics in production. Collaborate with Devlopers and MLOps engineers to ensure that pipelines are production-ready. Implement security, compliance, and governance practices. Support troubleshooting and incident response for deployed systems. Building relationships with ...

cases that cement and enhance this belief and deliver a positive impact in the world. Interested? The Fuzzy Labs team are experts on MLOps and in this publication we're going to tell you WTF it is, and why it is essential for building AI applications #J-18808-Ljbffr ...

technical designs throughout the project lifecycle. Experience with large-scale data initiatives, data labelling strategies, synthetic data generation and data quality management. Familiarity with MLOps practices and cloud platforms for AI deployment. Experience working with academic partners, research institutions, grant-funded programmes or collaborative research consortia. Experience contributing to bids ...

analytics Delivering production agentic systems, including RAG pipelines, vector search, and agentic frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, and n8n DevSecOps & DevOps MLOps Infrastructure as Code Building a truly diverse, equitable, and inclusive workplace is an ongoing journey, and were excited to keep learning and growing together. We have ...

technical designs throughout the project lifecycle.* Experience with large-scale data initiatives, data labelling strategies, synthetic data generation and data quality management.* Familiarity with MLOps practices and cloud platforms for AI deployment.* Experience working with academic partners, research institutions, grant-funded programmes or collaborative research consortia.* Experience contributing to bids ...

infrastructure automation. Hands-on work with Docker containers, security-focused architecture, and multi-provider integrations (cloud compute + frontier model providers) Familiarity with MLOps , model onboarding, compute orchestration, and infrastructure for large-scale AI usage Proficiency in Python and experience with additional languages Knowledge of Kubernetes, container orchestration, observability ...

fits into a drug‐discovery or materials‐design workflow, plus familiarity with cheminformatics tooling (e.g. RDKit, OpenEye) — or willingness to pick these up. MLOps fluency: experiment tracking, data versioning, model serving, and observability of deployed models. A visible track record in the field — peer‐reviewed publications, open‐source contributions ...

mentoring others or providing technical leadership.* Awareness of GDPR and international data regulations.**Useful, but not essential*** Causal inference and large-scale experiment design.* MLOps, including model registries, artefact versioning and drift monitoring.* Streamlit or similar tools for internal applications and dashboards.* Experience with claims, refunds or customer operations.You ...

cost management Model serving and inference at production scale (eg KServe, RayServe, Triton, vLLM, or similar) with real latency and cost constraints(preferred RayServe) MLOps pipeline tooling - training pipelines, model registries, feature stores, and lineage (Kubeflow, MLflow, Feast, Weights & Biases, or equivalents) LLMOps in production - inference serving, prompt/version ...

track record of developing and deploying models at scale Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes) With preferred backgrounds covering some of the following: Experience with speech-to-text or text ...

cloud data warehousing principles. Expertise with cloud data warehouse solutions such as Databrick, Snowflake or Redshift. Proven experience in DataOps, CI/CD (MLOps is a plus) Exceptional written, verbal, and listening communication skills, with the ability to effectively explain complex technical concepts to both technical and non-technical audiences. ...

CreateFuture seeks a Senior Data Engineer with an ML focus to own data and feature pipelines for production ML systems. You will collaborate with data scientists and ML engineers, mentor junior engineers, and elevate engineering ...

CreateFuture seeks a Senior Data Engineer with an ML focus to own data and feature pipelines for production ML systems. You will collaborate with data scientists and ML engineers, mentor junior engineers, and elevate engineering ...

CreateFuture seeks a Senior Data Engineer with an ML focus to own data and feature pipelines for production ML systems. You will collaborate with data scientists and ML engineers, mentor junior engineers, and elevate engineering ...

Hiscox is seeking an experienced Machine Learning Engineer to join a newly formed ML Engineering team. You will build and maintain infrastructure to deploy data‐driven models, and develop Python APIs to serve ML models ...

projects, prototype GenAI, RAG, and predictive models, and build scalable pipelines with data engineers and IT teams aligned to CI/CD and MLOps standards. The role requires an advanced degree and deep Python/SQL experience, plus the ability to communicate complex analytics #J-18808-Ljbffr ...

strong written and verbal communication skills. Experience in motorsport, high-performance engineering, automotive, manufacturing or other fast-paced technical environments. Knowledge of AI platforms, MLOps concepts, Microsoft Copilot, generative AI services, data platforms or enterprise AI governance processes. Experience in cloud managed endpoint management. We are an equal opportunities employer. ...

Scalable Pipelines:** Partner with data engineers and global IT teams to ensure AI solutions are scalable, secure, and integrated with CI/CD and MLOps standards.* **Bridge Tech and Strategy:** Translate complex algorithmic outputs and statistical concepts into clear, high-impact business strategies for senior stakeholders.* **Advance Technical Excellence:** Stay ...

including serving, monitoring, and retraining Experience leading or mentoring engineering squads Hands‐on experience building and training deep learning models in PyTorch Familiarity with MLOps tooling such as MLflow and CI/CD workflows Experience with AWS, Azure, or GCP Experience with sequence models (e.g. transformers, RNNs) or generative models ...

Snowpark, AWS Bedrock, SageMaker, vector search and semantic search architectures Experience delivering Business Intelligence platforms, self-service analytics solutions and working knowledge of DataOps, MLOps and LLMOps practices Demonstrable experience working in telecommunications and using industry best practice frameworks such as TM Forum, TOGAF, ITIL, BPMN and UML Life ...

Scalable Pipelines: Partner with data engineers and global IT teams to ensure AI solutions are scalable, secure, and integrated with CI/CD and MLOps standards. Bridge Tech and Strategy: Translate complex algorithmic outputs and statistical concepts into clear, high-impact business strategies for senior stakeholders. Advance Technical Excellence: Stay ...

advantage Experience implementing Responsible AI, AI Governance, Model Risk Management, or AI assurance frameworks. Experience deploying AI and machine learning solutions using MLOps, CI/CD, and production monitoring practices. Experience delivering AI solutions within regulated industries such as Financial Services, Government, Life Sciences, or Utilities. Experience contributing to business ...

You build the runway. Training pipelines, model registries, feature stores, evaluation, deployment, observability and cost governance - you turn ML from artisanal to industrial across every AutoThink product. What you'll build A shared ML/ ...