26 to 50 of 93 MLOps Jobs in London

operate and maintain AI development and production environments using Azure services, including AI, ML and GenAI workloads. Design and manage CI/CD and MLOps pipelines to support model development, deployment, monitoring and lifecycle management. Provision and secure cloud environments using Infrastructure as Code, with a strong focus on automation ...

Searches: ML Engineer/AI Engineer/Cloud Engineer/Machine Learning/Cloud AI/Google Cloud/GCP/Vertex AI/MLOps/ML Ops/AIOPs/AI Ops/ ...

related field Experience with genomics pipelines or tools (e.g. FASTQ, BAM, variant calling) Knowledge of protein structure modelling or drug discovery workflows Exposure to MLOps, deployment, and production systems Publications or open-source contributions in relevant domains Why Join Them Opportunity to work on genuinely impactful problems in healthcare ...

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, click apply for full job details ...

experience in training and deploying computer vision models into production · Proven track record with LLM fine-tuning, prompt engineering and productionisation · Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. · Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ...

stakeholders to prioritise backlogs, manage risks, and translate requirements into actionable technical plans. Establish and enforce engineering best practices -including coding standards, DevOps/MLOps pipelines, testing frameworks, and documentation-to ensure high-quality delivery. Drive innovation by evaluating emerging data and AI technologies, leading proofs of concept, and embedding ...

technical teams, with strong communication and collaboration skills. Awareness of data governance, secure handling of sensitive data, and regulatory considerations. Knowledge of MLOps/DevOps practices, including CI/CD pipelines for ML models. Understanding of reinforcement learning, multi-agent systems, or advanced optimization methods. Previous experience working in regulated ...

platforms, frameworks, and libraries Extensive experience with end-to-end model design and deployment within cloud environments ☁️ A systems thinking approach , with passion for MLOps best practises An engineer that can think in O(n) as much as plan the orchestration of their product. Solid understanding of data structures, data ...

working in cloud environments, ideally Azure. Solid understanding of software engineering fundamentals including APIs, distributed systems and secure system design. Experience with DevOps or MLOps practices such as CI CD, containerisation and monitoring. The confidence and gravitas to influence technical direction and guide a less mature AI function. A practical ...

coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming ...

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 ...

learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall, F1, Intersection over Union, and others. Additional beneficial ...

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 ...

traditional ML solutions end-to-end Comfortable in startup or scale-up environments — fast-moving, iterative, delivery-focused Strong Python engineering experience Experience with MLOps, CI/CD, IaC, and productionising ML models Ability to work collaboratively with product, data, and engineering teams Contract Details Location: Hybrid London ...

preferred) and experience with modern AI/ML frameworks. Proven experience delivering AI solutions in complex or high‐security environments. Desirable Skills Experience with MLOps, LLMOps, or production‐grade AI deployments. Knowledge of vector databases, RAG, and prompt engineering techniques. Exposure to government, defence, or national security domains. Who This ...

authentication/security best practices. A disciplined engineering mindset — you think about reliability, maintainability, and long-term scalability. Nice-to-haves Experience with MLOps and model-serving infrastructure. Background in high-performance computing or large-scale scientific workloads. Expertise in data pipeline architecture and real-time streaming systems. Knowledge ...

team environment Nice to Have Background in bioinformatics, computational biology, or life sciences Experience with drug discovery, protein modelling, or genomics pipelines Familiarity with MLOps, CI/CD, and scalable cloud infrastructure Exposure to graph-based models, transformers, or multimodal learning Experience in an early-stage startup or fast-scaling ...

your own on architectural trade-offs. You're fluent enough in the modern data and AI stack - Python, cloud-native services, event-driven architectures, MLOps tooling, LLM evaluation - to make informed product calls without relying on engineering to tell you what's possible. Salary and equity calibrated to the seed ...

iteration. Hands-on experience scaling a modern cloud data platform (lake/warehouse, orchestration, streaming). Deep understanding of the full ML lifecycle and MLOps/analytics engineering best practices. Experience implementing data architecture standards, data contracts, and governance across domains. Leadership experience managing managers and senior ICs within growing ...

PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research in machine learning are also beneficial. At a personal level we’re also looking for someone who is: Passionate about delivering software ...

requires someone who can engage with business stakeholders, design AI-driven architectures, and also contribute hands-on to development and deployment, particularly in AI MLOps environments. This is not a pure data scientist role or a pure BA role but a design + build + deploy role within Payments transformation … embedding AI into payments systems Work with data pipelines (real-time + batch) Implement data preprocessing, feature engineering, and model evaluation 4. AI MLOps & Deployment Set up and manage ML lifecycle using MLOps frameworks Implement: Model versioning CI/CD pipelines Monitoring & drift detection Governance and audit controls Ensure production ...

inference performance via batching, quantisation, distillation, LoRA/PEFT, accelerator utilisation (GPU/TPU), and efficient memory/latency tuning Build and maintain MLOps/LLMOps workflows-CI/CD for models and prompts, model registry/versioning, feature stores, and automated promotion across environments Instrument observability for data, models … Gateways and ISTIO, ability to Diagnose and intercept failures in End to End communication Implement best practices for data governance, security, and MLOps on GCP Proficiency with Python and common AI/ML frameworks such as TensorFlow, PyTorch, JAX, scikit learn, and Hugging Face libraries Knowledge of MLOps and LLMOps ...

Inside IR35 contract | 3-6 month 1-2 days onsite requirement London or Birmingham We are seeking an experienced MLOps Engineer with a strong background in DevOps, Data Science, or Machine Learning Engineering, who has hands-on experience productionising ML models. The focus of the role is building and enabling … itself. Candidates must have deep MLflow experience and proven delivery in real-world client settings. Key Responsibilities Design, build, and maintain end-to-end MLOps environments to support model training, tracking, deployment, and monitoring Implement MLflow for: Experiment tracking; Model registry; Model versioning and lifecycle management Enable model deployment into ...

their Series A and are a team of 20 with experience from companies like; Google DeepMind, Spotify, Sourcegraph & Meta. What We Are Looking For MLOps & DevOps Tooling: Proven track record of working with systems such as ArgoCD, Kargo, Jenkins, Vertex AI, SageMaker, and similar platforms. ML Infrastructure Experience: Proven track ...

work from home. The AI Engineer will support delivery of AI use cases, workflows, analytics and solutions - responsible for tasks such as pattern recognition, MLOps, software development, neural networks, and natural language processing on a day-to-day basis. Qualifications Pattern Recognition and Neural Networks skills Computer Science and Software ...