126 to 150 of 603 MLOps Jobs in England

scraping) built for continuous updates rather than one-off pulls. Monitoring and alerting across models and infrastructure (CloudWatch, Prometheus/Grafana, Sentry or similar; MLOps). AI and ML integration: productionising models (embeddings, LLMs); orchestrating LLM and NLP pipelines; ETL for training and inference data. Fluency with Claude Code ...

internal stakeholders.** *Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.** *Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.** *Experience of appropriate version control and environment management (such as venvs or Docker).** *Experience of writing technical project ...

internal stakeholders.** *Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.** *Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.** *Experience of appropriate version control and environment management (such as venvs or Docker).** *Experience of writing technical project ...

internal stakeholders.** *Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.** *Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.** *Experience of appropriate version control and environment management (such as venvs or Docker).** *Experience of writing technical project ...

stakeholders. Experience with Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks. Experience with vector databases, RAG architectures, and enterprise search solutions. Experience with MLOps, CI/CD, DevSecOps, and model lifecycle management. Understanding of data governance, Responsible AI, GDPR, and AI regulatory requirements. Experience working in regulated or complex ...

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 ...

architectures Practical experience with observability stacks (Grafana, Prometheus, OpenTelemetry) Experience with generative AI platforms: LLM hosting, LLM gateways (e.g.LiteLLM, Portkey, Kong AI Gateway), and MLOps/LLMOps practices for deploying and monitoring AI systems in production Strong stakeholder communication, translating architecture into business outcomes for senior stakeholders Preferred Skills ...

event-driven architectures.* Experience with Infrastructure as Code (e.g. CloudFormation, CDK, Terraform).* Any experience with MCP (Model Context Protocol) and/or MLOps (e.g. model deployment pipelines, monitoring and lifecycle management) is highly desirable.* Understanding of compliance requirement around SDLC, ITGC,ITAC.**Key Behavioural/Personality Traits**The Senior ...

familiarity or hands‐on experience with Salesforce CRM, Agentforce Studio, or Data Cloud (D360). Multi‐Modal & Advanced AI Frameworks: Experience with voice pipelines, MLOps, vector search, or custom model fine‐tuning. Location Based in London, UK (hybrid model). Education BS/MS in Computer Science, Artificial Intelligence, Engineering ...

retrieval systems Familiarity with scientific, biomedical, or scholarly datasets Experience with knowledge graphs, ontologies, or semantic enrichment systems Exposure to production ML systems and MLOps practices Academic or industry research experience in NLP, information retrieval, search, or generative AI Experience working in content-rich, knowledge-intensive, or highly regulated domains ...

rather than predictions aloneStrong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principlesAbility to lead end-to-end ML projects, work independently in ambiguous problem spaces, and mentor junior team membersStrong collaboration and communication skills, with experience ...

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 ...

open source, and helping customers achieve real outcomes. Nice to have Kubernetes, CUDA, TensorRT, ONNX, Jetson, or other edge accelerators. Experience with MLOps, model monitoring, CI/CD, or observability. Familiarity with AWS, Azure, GCP, serverless systems, or managed inference platforms. Experience integrating OpenAI or Anthropic APIs into customer tools. ...

third-party solutions to find opportunities for innovation and business value. Guide architectural decisions across AI platforms, model-serving infrastructure, data pipelines, and MLOps/LLMOps capabilities. Partner closely with Engineering teams to productionize AI solutions and drive operational excellence. Build, mentor, and lead high-performing teams of Data Scientists … native AI development using Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure AI Search, AWS AI Services, and modern cloud architectures. Experience implementing MLOps and LLMOps practices, including CI/CD, model lifecycle management, governance, and production operations at scale. COLLABORATION & COMMUNICATION Ability to communicate complex technical concepts clearly ...

Familiarity with data storage systems (e.g., Postgres, OpenSearch) and AWS services such as S3, SageMaker, and Bedrock Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps, Large Language Model Operations (LLMOps), Event Driven Systems. #J-18808-Ljbffr ...

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 ...

Azure preferred; AWS or GCP also considered) Strong programming skills in Python or similar languages commonly used in AI/ML Experience with LLMOps, MLOps, CI/CD for AI, Evaluation Driven Development and model monitoring in production Excellent communication and stakeholder management skills Experience supporting pre‐sales activities, including ...

maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (e.g. scikit-learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with LLMOps Exposure to cloud platforms (e.g. ...

model development and deployment of AI/ML applications in a production environment, with expertise in deploying models on AWS platforms. Deep familiarity with MLOps practices, covering the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models. Expertise in machine learning frameworks such as TensorFlow ...

Bedrock, SageMaker, OpenAI, Cognitive Services). Strong Python programming skills with hands‐on experience using frameworks like Autogen and LangGraph . Solid grounding in MLOps , containerisation (Docker, Kubernetes), and vector databases. Understanding of agent monitoring tools (Langfuse, OpenTelemetry). Strong software engineering best practices (testing, CI/CD, code reviews ...

Create frameworks, infrastructure and systems to manage and govern Ki’s data asset Work with the broader Engineering community to develop our data and MLOps capability infrastructure Strong experience in software engineering with proficiency in a language such as Python for API development, data engineering and automation tasks A background ...

familiarity or hands-on experience with Salesforce CRM, Agentforce Studio, or Data Cloud (D360). Multi-Modal & Advanced AI Frameworks: Experience with voice pipelines, MLOps, vector search, or custom model fine-tuning. Education: BS/MS in Computer Science, Artificial Intelligence, Engineering, or equivalent technical field. #J-18808-Ljbffr ...

Familiarity with Snowflake, Databricks, Azure AI Foundry , AWS SageMaker, and other leading platforms. Data Science Expertise: Knowledge of data science fundamentals, solution lifecycles, and MLOps methodology. Generative AI Knowledge: Experience with LLMs, neural networks, and recommendation systems. Frameworks: TensorFlow, PyTorch, Hugging Face, OpenAI tools. Certifications: Cloud or AI architecture certifications ...

cognitive architectures. Solid understanding of software engineering principles, including design patterns, data structures, and algorithms. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices is a plus. Excellent problem-solving skills, with the ability to translate complex business requirements into technical solutions. Strong communication and collaboration skills, with ...

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 ...