51 to 75 of 93 MLOps Jobs in London

particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform ...

Code CI/CD, automation, and platform reliability Running production workloads with high availability requirements Plus, experience with one or more of the following: MLOps or ML platform engineering RAG architectures, embeddings, or vector search Model serving, observability or performance optimisation Data/AI workflow orchestration in Databricks or similar ...

systems from the ground up. You’ll be responsible for: Defining the AI architecture and technical roadmap across LLMs, RAG, and agentic systems Owning MLOps infrastructure, including model monitoring, governance, and CI/CD pipelines Implementing Infrastructure-as-Code and ensuring robust, compliant AI systems in a regulated environment Ideal ...

pure manager) Nice to have FMCG/retail/commercial analytics experience (NIQ/Circana a plus) dbt/semantic layer design MLOps, evaluation & observability tooling Background in consulting or data science roles, now looking to own a product end-to-end Why this role is different Build real systems ...

looking for An experienced technology leader with a track record of successfully leading AI/ML strategy and project delivery. Strong understanding of MLOps, with experience deploying commercially valuable AI applications in financial services. Experience leading full-stack technology teams, with a solid grasp of systems architecture and engineering fundamentals. ...

simulation + tele‐op logs, version them, apply weak‐supervision labelling, curate balanced datasets, and auto‐surface fresh failure cases into retraining. Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‐time edge inference. We’re Looking For: 3+ years building deep‐learning systems ...

across the end-to-end delivery of machine learning systems. This includes building models, running experiments, and deploying scalable solutions using modern cloud and MLOps tooling. Key Responsibilities Include: Designing and developing machine learning models (e.g. classification, forecasting, anomaly detection) Supporting experimentation cycles: hypothesis definition, testing, and evaluation Contributing … PyTorch, TensorFlow, or XGBoost Exposure to AWS services (e.g. S3, Lambda, SageMaker) Understanding of core ML concepts: model evaluation, validation, and experimentation Familiarity with MLOps or experiment tracking tools (e.g. MLflow, Weights & Biases) Awareness of LLMs or generative AI concepts Strong problem-solving ability and willingness to learn ...

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. ...

development Solid understanding of anomaly detection techniques Experience building data workflows/pipelines Desirable: Experience working in secure/government environments Knowledge of MLOps best practices Familiarity with real-time or near real-time data processing Contract Details: Location: London (hybrid) Duration: 6 months Day Rate: Up to £595/ ...

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 ...

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 ...

practices across their ML and data setup, ensuring it is ready to support multiple enterprise deployments. Key responsibilities: * Audit current ML architecture, pipelines, and MLOps practices * Identify gaps in documentation, reproducibility, and scalability * Introduce clear structure across model development, versioning, and deployment * Improve training and retraining workflows * Strengthen model monitoring … Python and hands-on ML engineering experience * Proven experience in productionising ML systems end-to-end * Experience auditing and improving existing ML setups * Strong MLOps experience (model versioning, monitoring, CI/CD) * Experience working with data pipelines (ETL/ELT, Spark or similar) * Comfortable working with messy, real-world data ...

develop intelligent systems and tools Collaborating with cross-functional teams to integrate AI into production environments Conducting research, experimentation, and rapid prototyping Implementing MLOps best practices (CI/CD, monitoring, retraining pipelines) Translating business and stakeholder needs into scalable technical solutions Continuously improving AI/ML systems, frameworks, and performance … Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker, CI/CD, and version control ...

ready, with scalable infrastructure and clean, well-structured data pipelines Collaborate with data science and analytics teams to enable model deployment, automation, and MLOps best practices Promote innovation in generative AI, predictive analytics, and real-time decision support Align data architecture with security, compliance, and data governance requirements Lead … modern data integration tools. Excellent knowledge of Python, SQL, PowerQuery (M), and preferably Scala or PySpark Working knowledge with enterprise architecture frameworks (e.g., TOGAF), MLOps, and BI tools like Power BI and QuickSight Experience of generative AI platforms (e.g., Amazon Bedrock, Anthropic) Familiarity with infrastructure as code (Terraform), CI/ ...

underpin agentic workflows Own the end-to-end ML lifecycle from raw data and experimentation through to production deployment and continuous evaluation Lead MLOps infrastructure on AWS , building robust pipelines for training, monitoring, and retraining Bridge technical AI work with business strategy you'll have a seat at the table … solid TypeScript/API skills Hands-on experience with LLMs prompt engineering, evaluation, RAG architectures, safety considerations Cloud-native development on AWS and practical MLOps: CI/CD for models, version control, observability, retraining pipelines Familiarity with LangChain, Terraform, and modern AI tooling (Cursor, Gemini) is a strong plus Experience ...

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 ...

preprocessing, augmentation, and validation workflows. Run structured experiments, evaluate model performance, and iterate based on measurable results Build, deploy, and operate end-to-end MLOps pipelines, including experiment tracking, model versioning, and production monitoring. Package and deploy models using Docker and cloud infrastructure, with a focus on reliability and scalability … familiarity with the Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar). Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred) Practical experience ...

clear service boundaries Define enterprise-wide AI architecture guidelines, reusable components, and long-term roadmap to ensure consistency and acceleration of AI initiatives Implement MLOps/LLMOps pipelines for versioning, CI/CD, approvals, and controlled promotion across environments; enforce reproducibility Work closely with product owners, data scientists, engineers, security … Deep understanding of LLMs, generative AI, RAG patterns, vector databases, embeddings, and prompt/guardrail engineering Desirable Skills/Knowledge/Experience Knowledge of MLOps/AgentOps, CI/CD, and observability Strong understanding of regulated financial services environments Proven experience implementing AI risk controls, model governance, and auditability Ensure ...

clear service boundaries. Define enterprise-wide AI architecture guidelines, reusable components, and long-term roadmap to ensure consistency and acceleration of AI initiatives. Implement MLOps/LLMOps pipelines for versioning, CI/CD, approvals, and controlled promotion across environments; enforce reproducibility. Work closely with product owners, data scientists, engineers, security … Deep understanding of LLMs, generative AI, RAG patterns, vector databases, embeddings, and prompt/guardrail engineering. Desirable skills/knowledge/experience: Knowledge of MLOps/AgentOps, CI/CD, and observability. Strong understanding of regulated financial services environments. Proven experience implementing AI risk controls, model governance, and auditability. Ensure ...

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 ...

architecture to ensure reliability, scalability, cost-efficiency, and security. Build platform capabilities such as: Prompt versioning Evaluation dashboards Real-time user feedback systems Promote MLOps best practices and responsible AI by establishing robust monitoring, guardrails, and launch protocols. Mentor team members and contribute to a culture of engineering excellence through … etc.) or database internals. Proven track record of delivering end-to-end projects and mentoring engineers. Direct experience with ML platforms and MLOps is required. ...

transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low-latency, highly reliable cloud … strong hands-on use of ML/DL frameworks (e.g., PyTorch, TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure-as-code practices. Proven technical leadership experience including ...