101 to 125 of 226 MLOps Jobs in London

SuperSet, Tableau or PowerBI is a bo nus)Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring sys temsProven ability to create polished presentations and effectively communicate insights to customers with ...

Faculty is seeking a Platform Engineer to build the backbone of applied AI for its customers. You will design, build, and deploy robust, secure cloud infrastructure powering data and ML workflows. Work in a cross ...

Jobtailor in the United Kingdom seeks a senior leader to head Data Science and AI for the Economic Crime Hub, design scalable production-grade AI models, and own their end-to-end lifecycle. You will ...

SwiftCruit is seeking a Staff Software Engineer – Machine Learning to lead ML engineering initiatives while influencing technical strategy. You will drive AI adoption and collaborate with various teams, providing consultancy and mentorship to enhance technical ...

based models Building automated testing, retraining and deployment workflows Monitoring model performance, reliability and infrastructure Managing cloud and inference costs at scale Improving MLOps, CI/CD and engineering standards Working closely with Product, Data Science and Software Engineering teams The strongest candidates are likely to have: Strong commercial Python … engineering experience Experience deploying machine learning models into production Good knowledge of MLOps, model serving and monitoring Experience with AWS or another major cloud platform Docker and containerised application experience Infrastructure as code experience, ideally Terraform or CloudFormation Experience with SQL, PySpark, Databricks or AWS Glue Exposure to Scikit‐learn ...

/AI patterns, define and evangelise best practices, and establish reusable approaches that enhance delivery of AI use cases across the business Drive MLOps standards and practices across teams, including CI/CD for models, automated testing, monitoring, and deployment pipelines Collaborate with enterprise platform and data science teams, contributing … culture of continuous learning What we're looking for Deep expertise in Python and ML engineering Deep expertise in ML/AI systems design, MLOps, and cloud-native architectures Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience ...

stakeholders and helping shape technology and investment decisions. Mentoring architects and engineers, helping to develop capability across the wider team. Driving best practice across MLOps, AIOps, CI/CD and modern cloud engineering approaches. What we're looking for Extensive experience designing and delivering modern data platforms, analytics solutions ...

smart data plan optimization Define AI program roadmaps & pilots with clear business cases, data requirements, and phased delivery milestones Collaborate with data science and MLOps teams to move AI models from prototype to production within the IT platform Communicate AI initiative value and progress to executive sponsors through business-focused ...

Experience deploying machine learning models in Azure. Experience with modern AI or agentic AI frameworks. Experience working with cloud-based machine learning services or MLOps practices. Experience in transport, the public sector or another safety-critical industry. ...

networks, graph-based and sequence-based architectures Providing technical leadership to raise levels of expertise and best practices, including mentoring others Working with the MLOps team to drive tooling for rapid model iteration and lifecycle optimisation You should apply if What we’re doing at Monzo excites you. Multiple-year ...

such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers ...

10x Team is looking for a Freelance Machine Learning Operations Engineer – AI Trainer to work remotely with 8-20 hours a week commitment. You will help shape the future of AI by reviewing and enhancing ...

Engineer (LLMs/Azure/MLOps) Global Professional Services Firm Location: London Working: Hybrid (3 days office/2 days remote) Salary: Up to £85k + benefits The Role An exciting opportunity to join a global professional services organisation investing heavily in AI, with a focus on delivering enterprise-grade … services using retrieval, tool-calling and orchestration patterns Deliver end-to-end AI/ML pipelines covering experimentation, deployment, monitoring and optimisation Apply MLOps and LLMOps best practices across model lifecycle management, governance and production monitoring Work closely with Data Engineers, Platform Engineers and business stakeholders to deliver enterprise ...

create measurable impact. You're comfortable working across the full AI deployment lifecycle from use case discovery and solution architecture to multimodal agent development, MLOps pipeline implementation, and production optimization. You understand what makes agents perform well in production and how to systematically improve quality through observability and evaluation. Experience … custom SDKs (Python, TypeScript) Act as trusted technical advisor to customers, shaping AI strategy and guiding roadmap decisions from concept to production Data Strategy & MLOps Infrastructure Design data architectures with efficient processing pipelines and ingestion workflows for training and inference on aion's platform Implement RAG systems with vector databases ...

scalable ML pipelines and engineering frameworks AI model training, evaluation, optimisation and deployment Cloud-native AI and data platforms across Azure, AWS and GCP MLOps tools and best practices for deployment, monitoring and governance Structured and unstructured datasets Generative AI and advanced analytics solutions Designing and maintaining scalable data pipelines … cloud environments Knowledge of data engineering principles including ETL processes, data pipelines and automated workflows Experience working with structured and unstructured data Understanding of MLOps tooling and best practices Knowledge of data governance, security and compliance principles within AI and data environments Strong analytical and problem-solving ability Experience working ...

/AI patterns, define and evangelise best practices and establish reusable approaches that enhance delivery of AI use cases across the business. Drive MLOps standards and practices across teams, including CI/CD for models, automated testing, monitoring and deployment pipelines. Collaborate with enterprise platform and data science teams, contributing … culture of continuous learning. What we’re looking for Deep expertise in Python and ML engineering. Deep expertise in ML/AI systems design, MLOps and cloud‐native architectures. Track record of leading ML/AI technical initiatives across multiple teams. Strong experience with cloud platforms (AWS, Azure, GCP). ...

designing and building APIs, distributed systems, and event‐driven architectures in modern programming languages such as Python, TypeScript, Java, Go, or similar Familiarity with MLOps practices, model monitoring, observability, versioning, and automated deployment pipelines preferred Strong problem‐solving skills with the ability to navigate ambiguity, experiment rapidly, and deliver impactful … cost efficiency while supporting increasing AI adoption and usage Implement engineering best practices around observability, monitoring, testing, security, and operational excellence Establish and champion MLOps practices including model lifecycle management, prompt versioning, automated evaluation, and continuous improvement Build reusable frameworks, developer tooling, and platform capabilities that accelerate AI innovation across ...

UTA seeks a Principal AI Engineer to lead the design, development, and delivery of intelligent software systems that bring together enterprise application architecture, full-stack engineering, data science, and machine learning. In this highly visible ...

teams own the full delivery lifecycle, from early ideas through to production systems that create measurable impact for our customers and the business. As MLOps Engineering Manager, you will help shape how we build, deploy and operate machine learning products at scale, working closely with ML Engineers, Data Engineers, Software … Engineers, Data Scientists, Product Managers and stakeholders across Trainline. Responsibilities Build and lead a new team of MLOps Engineers, creating an environment where people can do their best work while delivering meaningful outcomes for customers and the business. Define and evolve MLOps processes, tooling and infrastructure choices across the technology ...

will span the full solution lifecycle—from assessing client needs to training, deploying, and monitoring models, with emphasis on scalable data pipelines, DevOps/MLOps, and collaboration with cross‐functional teams. #J-18808-Ljbffr ...

data scientists and product partners to transform innovative ideas into reliable, secure production systems. You'll design APIs, data pipelines, and deployment pipelines, applying MLOps practices, observability, and cost-efficient architectures while advancing AI capabilities across teams in a fast-paced, inclusive environment. #J-18808-Ljbffr ...

program management, or related roles Proven experience leading large-scale, cross-team projects Familiarity with the AI/ML lifecycle (model training, deployment, monitoring, MLOps) and AI/ML-based products or platforms Familiarity with Agile & Waterfall techniques (i.e PMP, PMI-ACP, Scrum) Experience in highly regulated or complex domains ...

ensure solutions are secure, ethical, and fit for purpose. Working across multidisciplinary teams, you'll drive innovation in areas like DevOps, platform engineering, and MLOps - balancing experimentation with governance and risk. What you'll be doing: Leading architecture, design, and delivery of digital & AI solutions Driving innovation across AI, analytics ...

monitoring, supportability and reliability concerns in production - Experience using infrastructure-as-code tools such as Terraform - Confidence taking responsibility for live systems and outcomes MLOps experience is highly attractive, particularly operating AI or machine learning models in production. The focus is on operating models, not training them. In Return ...

negotiating with health authorities (EMA/FDA). Proven track record building and deploying AI/ML systems, including model development, validation, MLOps, and production deployment. Deep understanding of AI architecture, data pipelines, model governance, and software engineering best practices. Experience collaborating with cross-functional teams across Engineering, Data Science ...