8 of 8 Remote/Hybrid MLOps Jobs in Central London

subject matter expert regarding GCP’s latest ML/AI tooling, and continuously prototyping and advocating for new tooling to ensure that our MLOps and AI infrastructure remains fit for purpose. Collaborating with Platform Engineering and Product to prioritise relevant workstreams across the Beatport Group. Working in conjunction with ...

multi cloud with strong AWS depth). Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components). Proven ability to take research and prototype environments ...

government, and national security. Working alongside Data Scientists, Software Engineers, and AI specialists, you'll take projects from experimentation through to production, leveraging modern MLOps and LLMOps practices on AWS to build scalable, secure AI systems. What You'll Be Doing Design, develop, and deploy machine learning models for traditional … frameworks. Lead experimentation cycles, defining hypotheses, running evaluations, and iterating on models before production deployment. Develop robust ML pipelines using AWS services and MLOps tooling. Implement experiment tracking, model versioning, monitoring, and reproducibility best practices. Build feature engineering pipelines and contribute to feature store development. Monitor production models, optimise performance ...

workflows. Oversee the full technical lifecycle, from solution design and model selection through to deployment, monitoring and continuous improvement. Design and implement robust MLOps and LLMOps practices, including CI/CD, model monitoring, evaluation and governance. Deploy and optimise models using cloud-based AI services such as AWS Bedrock, Azure … LangChain, LangGraph or similar open-source AI toolkits . Experience fine-tuning, evaluating, deploying and monitoring large-scale AI systems. Strong understanding of MLOps and/or LLMOps , including CI/CD, model deployment, monitoring, evaluation and governance. Experience designing AI systems with a strong focus on security, responsible ...

/ML lifecycles **Strong experience with data quality, metadata management, master data management, knowledge graphs, or data products **Familiarity with Generative AI, MLOps, AI governance, model risk management, and responsible AI frameworks Bonus: **Background in financial services, risk, ratings, or regulated data environments Immediate start date. If interested, please apply ...

systems tailored to audit applications. Contribute to architectural decisions and solution governance. Write clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable … development patterns, enforcing coding standards, and implementing MLOps best practices that support version control, performance optimisation, and maintainability. Cross-Disciplinary Collaboration: Work side-by-side with data scientists, product managers, platform engineers, and QA teams to align on technical requirements, delivery timelines, and integration plans. Provide hands-on contributions ...

bigger strategic programmes Solid AWS experience - S3, Lambda, EventBridge, SNS/SQS Comfortable working across TOGAF, ArchiMate, C4, UML and BPMN Hands-on with MLOps tooling and platforms - SageMaker, OpenVINO or equivalent Experience architecting data for large volumes of imagery - tiering, retention, lineage, provenance Familiar with the governance side ...

production-grade Machine Learning solutions , building scalable AI systems that solve complex real-world challenges. Design end-to-end ML architectures , including model development, MLOps pipelines, deployment strategies and continuous optimisation. Collaborate with engineering, data and product teams to deliver robust, production-ready AI solutions using modern ML and software … have taken models from development through to production. Experience with areas such as: Python and modern software engineering practices Machine Learning/Deep Learning MLOps and production ML systems Cloud platforms and scalable infrastructure ML frameworks such as PyTorch, TensorFlow or equivalent LLMs/Generative AI is highly desirable ...