101 to 125 of 603 MLOps Jobs in England

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 ...

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 ...

production ML or data engineering experience considered. 8+ years of hands‐on experience building, deploying, and operating production ML systems on Azure, with practical MLOps and CI/CD experience including experiment tracking, deployment hygiene, monitoring, evaluation, and operational documentation. Strong Python and software engineering fundamentals, including testing, version control ...

Azure) and their data services. Tool & Product Development: Hands-on experience in developing and maintaining analytical tools, dashboards, and automated solutions. Familiarity with MLOps principles and practices for productising data science models. AI & Generative AI: Proven ability to identify and implement AI-driven solutions to enhance analytical capabilities and efficiency. ...

preparation, feature engineering, and feature stores, and understand why reproducibility and point-in-time correctness matter more than they first appear Have worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ...

preparation, feature engineering, and feature stores, and understand why reproducibility and point-in-time correctness matter more than they first appear Have worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ...

preparation, feature engineering, and feature stores, and understand why reproducibility and point-in-time correctness matter more than they first appear Have worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ...

/IEC 42001, andNIST AI RMF. Experience working closely with cybersecurity, legal, and risk teams to ensure compliance and audit readiness. Strong background in MLOps and DevSecOps, including CI/CD pipelines, model monitoring, drift detection, and infrastructure‐as‐code. Skills : Ability to lead complex AI engineering programmes, set technical ...

PyTorch, or TensorFlow Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles Ability to lead the end-to-end lifecycle of ML initiatives, work independently in ambiguous problem spaces, and mentor and grow other scientists ...

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 ...

/CD pipelines. Practical data science experience building statistical and machine learning models, including feature engineering, hyperparameter tuning. Experience productionising ML and GenAI solutions (MLOps): deploying end-to-end model pipelines and establishing evaluation, benchmarking, and continuous monitoring frameworks. Experience leveraging GenAI technologies to build data solutions. Ability to communicate ...

/CD pipelines. Practical data science experience building statistical and machine learning models, including feature engineering, hyperparameter tuning. Experience productionising ML and GenAI solutions (MLOps): deploying end-to-end model pipelines and establishing evaluation, benchmarking, and continuous monitoring frameworks. Experience leveraging GenAI technologies to build data solutions. Ability to communicate ...

Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands‐on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms (Azure, AWS or GCP) Experience deploying AI solutions within government, defence, healthcare or other high‐assurance environments Strong understanding ...

Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms (Azure, AWS or GCP) Experience deploying AI solutions within government, defence, healthcare or other high-assurance environments Strong understanding ...

Cluster management Unity Catalog Preferred Skills Databricks Certified DataEngineer Professional/Databricks Certified Architect. Experience with: MLflow Databricks Machine Learning Feature Store Model deployment MLOps Knowledge of streamingtechnologies: Structured Streaming Kafka Experience with datagovernance, compliance,and enterprise securityframeworks. Key Competencies Strong Databricks architectureand implementation expertise. Ability to designscalableand cost-efficientLakehouse ...

stakeholders, and scale successful solutions into production. Own the data platform strategy, ensuring well-governed data underpins AI and analytics initiatives. Establish robust MLOps and engineering practices covering deployment, monitoring, experimentation and governance. Champion practical AI adoption across Product and Engineering to improve ways of working. Build, lead and develop ...

development Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and LLMs #J-18808-Ljbffr ...

security controls. Experience integrating AI solutions with Microsoft 365 technologies, collaboration platforms, and SQL-based databases. Desirable Experience AI governance and responsible AI frameworks. MLOps and LLMOps tools and methodologies. Prompt engineering and model fine-tuning. Agentic AI frameworks such as LangGraph, AutoGen, or CrewAI. AI orchestration platforms such ...

engineers, data scientists, and ML practitioners. Experience with AWS and infrastructure-as-code tools such as Terraform. Experience in multi-agent orchestration. Familiarity with MLOps practices, including CI/CD for ML, model monitoring, automated deployment, and ML pipelines. Experience with agentic telemetry and evaluation services. Experience in customising ...

others Build data pipelines and feature engineering jobs on Databricks to prepare payments data for model training and agent retrieval Contribute to the MLOps path for optimization and prediction models, including training jobs, automated tests, and promotion of model artefacts from development through UAT to production Write evaluations for agent ...

influence and advise executive stakeholders up to C-level Deep expertise in artificial intelligence, machine learning and generative AI applications with strong knowledge of MLOps and LLMOps lifecycles Advanced understanding of cloud-scale data platforms such as AWS, Azure, GCP or Databricks and data engineering best practices Knowledge of data ...

conversations - discovery, whiteboarding, architecture reviews Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics Strong presentation and demo skills - you will build and present a live solution during the interview Bachelor's or Master's degree ...

ability to work effectively across technical and business teams. Passion for innovation, continuous improvement and emerging data technologies. Desirable Experience with Scala. Exposure to MLOps, feature stores and machine learning platforms. Our Benefits Hybrid working - 2 days in the office and 3 days working from home 25 days annual leave ...

making pragmatic architectural trade-offs. Strong cloud experience, ideally within Azure. Experience deploying, monitoring and maintaining ML or LLM models in production. Familiarity with MLOps, LLMOps, evals, monitoring and lifecycle management. Hands-on experience orchestrating LLM workflows using frameworks such as LangChain. An interest in how agentic software development ...

experience with distributed computing with Apache SparkTM and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines ...