151 to 175 of 409 MLOps Jobs in London

loops, and technologies such as Gemini, Claude and OpenAI APIs. Hands‐on experience with AI tools/frameworks (e.g., Braintrust, AutoEval) and/or MLOps tools (e.g., Airflow, MLflow, Vertex AI, or similar). Solid understanding of data engineering practices, including ETL, batch/streaming pipelines, and data quality monitoring. ...

agent frameworks , vector databases , and LLM orchestration tools . Ability to lead multi-disciplinary teams and manage complex AI projects. Advanced proficiency in Python , MLOps, and software engineering principles. Experience setting technical standards, governance frameworks , and performance benchmarks. Strong consulting mindset with the ability to translate emerging technology into business ...

release processes for ML or other production software systemsExperience deploying, serving and operating machine-learning models in production environments3-7 years’ professional experience in MLOps, ML platform engineering, ML infrastructure, backend engineering, DevOps or SREStrong understanding of observability, monitoring, alerting, incident response and common failure modes in ML systemsStrong production ...

cross‐functional work collaborating with other teams. Strong communicator – able to explain complex technical concepts to different audiences. Experience in one or more of: MLOps for Kubernetes‐based clusters Building production systems with large language models Efficient computing based on low‐precision arithmetic. Experience writing C++/Triton/CUDA ...

loops, and technologies such as Gemini, Claude and OpenAI APIs. Hands-on experience with AI tools/frameworks (e.g., Braintrust, AutoEval) and/or MLOps tools (e.g., Airflow, MLflow, Vertex AI, or similar). Solid understanding of data engineering practices, including ETL, batch/streaming pipelines, and data quality monitoring. ...

frameworks such as TensorFlow/PyTorch. Proficiency with Python and strong software development background. Knowledge and experience with AWS is highly desirable. Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable. Ability to communicate complex technical concepts clearly to non-technical stakeholders. Why Work for Proximie ...

Vault, cloud-native equivalents), OPA/policy-as-code, SBOM and SLSA concepts. Platform: Kubernetes, containers, Terraform, service mesh, observability stacks AI/ML: MLOps and LLMOps tooling, model registries, vector stores and retrieval architectures, evaluation frameworks, agent frameworks, AI gateway patterns Experience operating under model risk management (e.g. ...

with Engineering and Data colleagues to turn model outputs into reusable, scalable data assets rather than one-off analysis or tables . Partner with MLOps colleagues to deploy, monitor and retrain models, with clear ownership, versioning in MLflow and documented handover points. Turn complex model outputs into clear, commercially relevant ...

access expectations. Experience with PETs or privacy‐preserving ML frameworks such as Flower, Opacus, TensorFlow Federated or similar. Cloud platforms, containerisation, CI/CD, MLOps or production ML systems. Experience evaluating synthetic data using both utility and privacy metrics. Hiring Process We feel hiring should be transparent and give ...

Anaplan Inc. seeks a Platform Lead to spearhead ML Ops infrastructure, cost-optimisation, and deployment strategies. You will manage a talented DevOps team while remaining deeply technical and hands-on, building scalable platforms for ML ...

Proximie is seeking an experienced ML Platform Engineer to own the productionization and scaling of the machine learning stack. You will manage platform infrastructure, model training and inference on AWS SageMaker, and ensure reproducible, observable ...

indexing and retrieval. Build and maintain dataprocessing pipelines using Databricks and Apache Spark. Support the development,testing and deployment of machine learning models through MLOps pipelines. Develop user-facing AIinterfaces, including streaming interactions and human-in-the-loopworkflows. Implement automated testing, AImodel evaluations and CI/CD processes to ensure … within Agiledevelopment environments. Understanding of securesoftware development practices and responsible AI principles. Nice to Have Experience with AWS cloudservices. Hands-on experience withDatabricks and MLOps frameworks. Knowledge of Model ContextProtocol (MCP) and AI agent orchestration. Experience with AI evaluationframeworks, LLM-as-a-judge techniques and automated regression testing. Familiarity with ...

generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation, creating resilient data pipelines, scalable deployment architectures and automated ML workflows using contemporary engineering and CI/CD practices, enabling AI solutions … learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It’s all live lectures, tutor-led group work and real-world challenges from day one. Learn it. Apply it. Keep going Your ...

Job Role: Customer AI Engineer Team: Song AI & Data – AI & Modelling Craft, UK&I Location: London/Manchester Career Level: Consultant (L9) We Are Accenture Song accelerates growth and value for our clients through sustained ...

governance Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML End‐to‐end custom SageMaker pipelines for recommendation systems Design and implement the engineering components of GAR+RAG systems … problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure Requirements Extensive experience ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production Strong Python, Java, and/or Scala engineering Experience with statistical analysis, machine learning theory ...

while collaborating with Data Scientists to integrate AI/ML into banking systems. You will architect scalable cloud infrastructure on AWS with Kubernetes, promote MLOps practices, and mentor junior engineers to drive automation and reliability across production systems. #J-18808-Ljbffr ...

Platform Engineer to design and operate an Azure-based data and AI platform. The role covers Azure landing zones, network architecture, Databricks governance, and MLOps pipelines. You will implement secure, scalable infrastructure and CI/CD processes for global teams. The candidate will work hands-on with Terraform, Bicep, Azure ...

applications. You’ll drive end-to-end development from discovery to production, work across voice, vision, and text, and leverage LangChain, LlamaIndex, and modern MLOps on AWS/Azure/GCP to deliver scalable, observable AI solutions at scale. #J-18808-Ljbffr ...

with production deployments Strong Python (pandas, scikit-learn, PyTorch) and SQL Solid grounding in statistics, experimentation and causal inference Experience with at least one MLOps stack (MLflow, SageMaker, Vertex) Nice to have Published research or Kaggle competition experience Domain depth in financial services, retail or healthcare Send your ...

architectures Qualifications 7+ years in enterprise architecture or AI/ML engineering Experience with cloud environments (AWS, Azure, GCP) Knowledge of AI governance and MLOps tools Work Environment A truly hybrid and flexible working environment, with the chance to shape how AI-\u2011driven advisory is delivered — working on cutting-\u2011edge ...

architectures Qualifications 7+ years in enterprise architecture or AI/ML engineering Experience with cloud environments (AWS, Azure, GCP) Knowledge of AI governance and MLOps tools Work Environment A truly hybrid and flexible working environment, with the chance to shape how AI-driven advisory is delivered — working on cutting-edge ...

quantitative discipline, e.g. Computer Science, Mathematics, Statistics Track record of developing, deploying business critical machine learning models Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc Experience monitoring, maintaining, enhancing existing models over an extended time period Specialism in NLP or Computer Vision Solid understanding of fundamentals of statistics ...

technology services or consulting environmentsProven track record delivering complex data, analytics or AI programs at scaleHands-on experience with AI/ML delivery including MLOps, data pipelines and AI SDLC frameworksAdvanced stakeholder management skills with experience engaging C-level executives and engineering teamsFamiliarity with multi-geography delivery models and distributed ...

practices CI/CD pipeline management Infrastructure as Code (IaC) Nice-to-Have Hands-on experience with: Data Quality Data Governance techniques Knowledge of: MLOps Feature Engineering Exposure to data analysis and ML tools such as: scikit-learn pandas NumPy XGBoost LightGBM Familiarity with orchestration tools: Apache Oozie Apache Airflow ...

related field, or equivalent practical experience. Desirable Experience with financial services or other regulated industries. Contributions to open-source projects. Experience with MLOps and the deployment of machine learning models. What we’ll provide you This is a unique role that will put you in the position to be part ...