26 to 38 of 38 MLOps Jobs in Central London

ongoing BAU support and maintenance of data structures, schema, reporting etc. Work with the broader Engineering community to develop the client's data and MLOps capability infrastructure Ensure data quality, governance, and compliance with internal and external standards. Monitor and troubleshoot data pipeline issues, ensuring reliability and accuracy. ...

predictive analytics — helping the world's largest employers find the right people, faster and fairer. But we're not done. Not even close. Role: MLOps Engineer Location: Remote Industry: Technology/AI & ML Infrastructure Job Function: MLOps/ML Platform Engineering Role Overview: We are hiring an MLOps Engineer ...

impact, working with diverse data types - including text, images, audio, video, and geospatial data - while applying cutting-edge methods in AI, machine learning, and MLOps/LLMOps practices. You'll have the opportunity to: Work alongside leading data scientists, ML engineers, and AI researchers on national security projects Design, develop … traditional ML use cases and GenAI/LLM applications Explore and implement ML and LLM models on complex, multi-modal datasets Apply modern MLOps/LLMOps practices, including experiment tracking, versioning, and deployment on cloud platforms Influence technical direction and best practice in ML and AI engineering Mentor and support ...

discovered and developed. We’re looking for senior candidates with deep expertise in: • Deep learning and modern ML systems • Distributed training and GPU infrastructure • MLOps, deployment, and reliability at scale • Biomedical, genomics, or drug discovery ML Requirements 7+ years relevant post PhD experience Experience productionising foundation models and model components ...

design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning … data preprocessing pipelines Monitoring, optimising and maintaining deployed models for performance, cost and reliability Implementing explainability, fairness and bias-mitigation strategies Collaborating on MLOps pipelines, CI/CD workflows and production deployments Mentoring junior engineers and promoting best practices across the team Staying current with advances ...

resource plans, timelines, and risk frameworks 🏗 Design AI Architectures Translate requirements into scalable AI/ML solutions Design architectures covering: Model development Data pipelines MLOps and monitoring Cloud integration (Azure, AWS, or GCP) Validate feasibility with engineering and delivery teams ✍️ Lead Tender & Bid Responses Own technical sections of AI RFPs … capability in scoping AI/ML programmes and estimating effort Deep understanding of: Machine learning (supervised & unsupervised) Generative AI & LLMs Embeddings, vector databases, RAG MLOps and model lifecycle management Experience with platforms such as: Azure ML, AWS SageMaker, Google Vertex AI Databricks, LangChain, Hugging Face Ability to develop architecture artefacts ...

Job Title Senior Data Scientist - CRM Location London – hybrid working (2/3 days in City offices) Salary To c£75,000 negotiable DoE Job Reference J13015 POSITION OVERVIEW We are super excited to be ...

needed for this role: Expert AI/ML Skills Strong in both traditional ML and modern LLM/RAG/agentic workflows Production Deployment & MLOps Comfortable shipping scalable AI systems using APIs, microservices, Docker/Kubernetes, and cloud (GCP ideal) Business Partnering Able to translate business needs into clear technical … LlamaIndex, etc.) Proven track record of deploying AI applications into production environments Strong understanding of API development, microservices, and containerization (Docker, Kubernetes) Knowledge of MLOps best practices Excellent problem-solving skills and ability to work in a fast-paced environment So, whats in it for you? Bonus Schemes A bonus ...

adoption of large language models (e.g. Gemini) to enable intelligent automation and natural language interactions. You will also define best practices across data engineering, MLOps, and LLMOps, ensuring scalable, secure, and high-quality solutions. Working closely with Architecture, Risk, and Compliance teams, you will ensure responsible and compliant AI deployment. … native data platforms (BigQuery) Deliver batch and real-time pipelines (Dataflow, Pub/Sub, Cloud Storage) Drive AI and LLM-based automation initiatives Implement MLOps and LLMOps best practices Set standards for data quality, security, and resilience Lead and develop data and AI engineering teams Collaborate with stakeholders across ...

Machine Learning Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of ...

I am recruiting for a Data Scientist to work on a hybrid basis - 2-3 days in London, remaining time remote. The role falls inside IR35 so you will be required to work through an ...

Machine Learning Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of ...

client is a leading global software platform company transforming how modern organizations build, secure, and deliver software across DevOps, DevSecOps, and MLOps environments. Trusted by thousands of enterprises worldwide including many of the largest global organizations the platform plays a critical role in securing and accelerating software delivery from code … Bitbucket) Security technologies such as SCA, SAST, SBOM management, and container security Background in software development is a strong advantage Experience or exposure to MLOps is a plus Diversity & Inclusion Our client is committed to fostering a diverse, inclusive, and equitable workplace . They believe that diverse perspectives drive better ...