51 to 75 of 197 MLOps Jobs in London

tools like Spark, Hive or Redshift A track record of leading cross-functional teams and communicating technical concepts to non-technical audiences Experience with MLOps practices - CI/CD, model monitoring, DevOps integration ADVERT DISCLAIMER Research indicates that men will apply to a role when they only meet ...

associated architecture patterns Experience designing and managing APIs including REST and GraphQL Strong understanding of microservices and serverless architectures Practical experience with DevOps and MLOps practices including CI/CD pipelines Knowledge of security frameworks, identity management and authentication standards Desirable Skills for the AI Solutions Architect: Experience with enterprise ...

engineers, business stakeholders) to define project scope, interpret model results, and clearly present data-driven recommendations to both technical and non-technical audiences. Deployment & MLOps: Collaborate with ML/Data Engineers to deploy, monitor, and maintain ML models in a production environment, ensuring stability and performance over time. Required Skills ...

Willingness to work on‐site in our Alkmaar office Nice to Have (But Not Required) Experience deploying ML models into production environments Familiarity with MLOps tooling such as MLflow, CI/CD workflows, and model monitoring Experience with AWS, Azure, or GCP Understanding of real‐time systems, motion synthesis ...

successful deployment and adoption across the business. Take ownership of AI-enabled products, from early concept and prototyping through to production and scaling (including MLOps). Align AI initiatives with business objectives, defining use cases, and ensuring solutions deliver meaningful commercial value. Build strong relationships with stakeholders and external partners ...

assistants. Familiarity with scientific, biomedical, or scholarly datasets and workflows. Experience with knowledge graphs, ontologies, or semantic enrichment systems. Experience with production ML systems, MLOps, and AI governance practices. Publications or applied research contributions in NLP, IR, search, recommendation systems, or generative AI. Experience building AI systems in high‐trust ...

agentic frameworks (e.g., LangChain, LlamaIndex, Crew AI, AutoGen, n8n), ensuring scalable, production‐ready solutions that empower developers and align with business outcomes. DevSecOps & DevOps MLOps Infrastructure as Code Data Engineering: including platforms like Databricks for data processing and analytics. Building a truly diverse, equitable, and inclusive workplace is an ongoing ...

related fields. Strong knowledge of AI, machine learning, deep learning, and probabilistic modeling. Proficient in Python, PySpark, data modeling, and microservices. Experience in MLOps, AI lifecycle management, and LLM orchestration on cloud platforms (AWS, GCP, Azure). Familiar with DevOps tools (Azure DevOps, GitHub Actions, Jenkins, Terraform, AWS CloudFormation). ...

automation workflows • Build scalable APIs, backend services, and integrations • Define and mature the organisation’s AI architecture and engineering standards • Implement robust DevOps/MLOps practices for AI systems • Mentor engineers and improve AI delivery capability across the team • Work closely with product and business stakeholders to shape ...

Working closely with product, engineering, and business stakeholders to define requirements and trade offs. Deploying models using cloud infrastructure, CI/CD pipelines, and MLOps best practices. Taking responsibility for monitoring, performance, and ongoing improvement of live models. Your Skills and Experience Strong commercial data science experience with a solid ...

processes Familiarity with cloud platforms, particularly Microsoft Azure Understanding of microservices architecture and distributed systems Experience with DevOps practices for AI/ML workflows (MLOps) Strong programming skills in Python and related data science libraries Demonstrated ability to work within solution architecture frameworks Preferred Qualifications Experience with multiple cloud providers ...

Adaptive Decision Manager in production environments is highly desirable. * Exposure to real-time decisioning, customer engagement, or personalisation use cases is advantageous. * Familiarity with MLOps practices and model monitoring frameworks is beneficial. How to Apply If you are looking for a senior data science role where you can combine technical ...

OpenAI, Document Intelligence (Form Recognizer), and Cognitive Search. Data Engineering: Expert proficiency in Python and PySpark for large-scale data processing. Operations: Familiarity with MLOps or LLMOps frameworks to support production-grade AI. Seniority: 15+ years of total IT experience, showing a clear progression into technical leadership. Candidate Profile Must ...

OpenAI, Document Intelligence (Form Recognizer), and Cognitive Search. Data Engineering: Expert proficiency in Python and PySpark for large-scale data processing. Operations: Familiarity with MLOps or LLMOps frameworks to support production-grade AI. Seniority: 15+ years of total IT experience, showing a clear progression into technical leadership. Candidate Profile Must ...

copilots/agents (e.g., vibe coding) to validate value and architectural fit Core Skills AI/ML and GenAI fundamentals (LLMs, RAG, AI agents, MLOps) Business consulting, problem framing, and architecture-to-value storytelling Program leadership and stakeholder management across product, engineering, and architecture teams Commercial acumen and deal shaping ...

including vector embeddings , rerankers , and data indexing in databases like MongoDB. Practical knowledge of LLM fine-tuning, prompt engineering, and performance optimization. Familiarity with MLOps principles and tools, including CI/CD with GitHub Actions . A strong interest in computer vision and an understanding of object detection models like ...

Synapse, BigQuery) Ensure robust data engineering practices (Airflow, dbt, Prefect) and governance (Collibra, Purview) Drive scalable lakehouse architectures (Delta Lake, Iceberg, Hudi) Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and CI/CD pipelines Ensure scalable deployments … across academia, startups, and hyperscalers Your Background Proven experience leading enterprise-scale AI transformation programmes Deep technical expertise across Python, .NET, cloud platforms, and MLOps Strong understanding of data governance, architecture, and DevSecOps Demonstrated ability to deliver measurable business outcomes and ROI Exceptional stakeholder management and executive communication skills Additional ...

deployment models across enterprise environments Advising clients on suitable AI use cases and opportunities for enterprise-wide adoption Collaborating with Enterprise Architects, Data Scientists, MLOps Engineers, DevOps teams and business stakeholders to shape and deliver solutions Selecting and implementing appropriate cloud, open-source and commercial AI technologies Leading the delivery … hosting Retrieval Augmented Generation (RAG), vector databases, semantic search and embedding techniques Python development and AI frameworks such as PyTorch, TensorFlow and LangChain MLOps frameworks and AI model lifecycle management API integration and enterprise-wide AI solution delivery Presenting architecture solutions to senior stakeholders, governance forums and architecture boards ...

Looking for experience with: ✔ Python ✔ PyTorch/TensorFlow/Scikit-learn ✔ Production ML systems ✔ AWS/GCP/Azure Bonus points for MLOps, signal processing, maritime or offshore energy experience. If interested, please apply or message directly. ...

Excellent experience as a, ML, or AI Engineer, with evidence of shipping production systems Strong Python skills and experience with FastAPI Experience working modern MLOps tools, ideally Kubeflow Strong experience working closely with LLMs (including fine-tuning, RAG, prompt engineering) Strong problem-solving skills and ability to communicate technical trade ...

capabilities to ensure solutions are secure, well-governed, and scalable. Engineering Excellence: Establish and enforce best practices for the automated SDLC, including DevOps/MLOps pipelines , coding standards, and rigorous testing frameworks. Stakeholder Synthesis: Translate complex business requirements from product owners and stakeholders into actionable, high-level technical plans ...

product selling. Demonstrated success in selling: Generative AI and LLM-based enterprise solutions Predictive and prescriptive analytics Intelligent Automation (RPA + AI) Data Engineering, MLOps, and AI platforms Ability to articulate AI ethics, governance, security, and compliance considerations. Experience selling Managed AI Services and AI-as-a-Service models. Ability ...

product selling. Demonstrated success in selling: Generative AI and LLM-based enterprise solutions Predictive and prescriptive analytics Intelligent Automation (RPA + AI) Data Engineering, MLOps, and AI platforms Ability to articulate AI ethics, governance, security, and compliance considerations. Experience selling Managed AI Services and AI-as-a-Service models . ...

that allow their applied AI team to ship production LLM applications without breaking things. The focus is infrastructure engineering for AI systems — not traditional MLOps or feature engineering. You'll be responsible for: Multi-modal data pipelines — Ingesting video, audio, and structured data at scale; designing processing infrastructure that handles ...

stakeholders to translate business requirements into actionable technical solutions , manage delivery risks, and prioritise backlogs. Establish and enforce engineering best practices , including DevOps/MLOps, coding standards, testing frameworks, and documentation. Design and deliver innovative, scalable, secure, and sustainable solutions aligned with industry standards. Facilitate workshops and stakeholder engagement sessions ...