51 to 73 of 73 MLOps Jobs in London

solve the most complex challenges in high-DOF autonomous systems and embodied AI. We are looking for experts across: AI/Machine Learning MLOps Software Engineering Data Science The Environment The mission is driven by high-bandwidth, in-person collaboration. This is a 5-day-a-week, onsite role ...

technical and non-technical stakeholders Eligible for or holding SC clearance Desirable Experience: Familiarity with government AI standards, frameworks, or compliance requirements Experience with MLOps, monitoring, and evaluation of AI systems Prior consulting experience in central government or highly regulated sectors Reasonable Adjustments: Respect and equality are core values ...

with sensor selection, placement, and calibration. Expertise in training and fine-tuning models for perception in novel or domain-shifted environments; Solid foundation in MLOps, including dataset management, training infrastructure, and deployment pipelines. Nice to have: Experience in construction robotics, heavy machinery, or large-scale manipulation tasks. Familiarity with vision ...

Senior MLOps & Platform Engineer I'm working with a London-based AI company building Real Time, production-grade AI systems for the financial sector. They're focused on practical applications of machine learning and LLMs, with products already in use by trading and investment teams. They're now looking … Senior MLOps & Platform Engineer to take ownership of the infrastructure and platform layer that supports their machine learning workloads. Role : Senior MLOps & Platform Engineer Rate : £500 - £625 per day Duration : 6 months Location : London The role This is a hands-on engineering role focused on building, running, and scaling ...

Engineer to help deploy AI/ML solutions into production environments across a range of client engagements. This role is focused on operationalising models (MLOps/AIOps), rather than building ML applications from scratch. Key Responsibilities Design and develop machine learning operational processes across diverse client environments Analyse client requirements … using AWS CDK Collaborate closely with data scientists to productionise ML models Required Experience & Skills Proven experience deploying AI/ML models into production (MLOps/AIOps) Strong AWS experience (other cloud platforms will not be considered) Experience with CI/CD pipelines for ML/DL models Proficiency ...

Engineer to help deploy AI/ML solutions into production environments across a range of client engagements. This role is focused on operationalising models (MLOps/AIOps), rather than building ML applications from scratch. Key Responsibilities Design and develop machine learning operational processes across diverse client environments Analyse client requirements … using AWS CDK Collaborate closely with data scientists to productionise ML models Required Experience & Skills Proven experience deploying AI/ML models into production (MLOps/AIOps) Strong AWS experience (other cloud platforms will not be considered) Experience with CI/CD pipelines for ML/DL models Proficiency ...

model orchestration, inference services and application integration Architect and deploy LLM solutions (GPT, BERT, Transformers) including RAG pipelines and vector databases Lead LLMOps/MLOps strategy including model lifecycle, CI/CD for ML, model registry and monitoring Design scalable cloud-native AI solutions in Azure, AWS or GCP Ensure … Strong cloud experience: Azure OpenAI, AWS Bedrock/SageMaker or GCP Vertex AI Experience with Kubernetes, Docker, microservices, API integration Strong knowledge of Python, MLOps, LLMOps, CI/CD, model monitoring Experience delivering enterprise AI solutions at scale Desirable Experience with vector databases (Pinecone, FAISS) AI governance, compliance and security ...

Predictive modelling for customer churn, asset failure, or sales performance Full ML life cycle ownership: prototyping deployment monitoring Building production-ready pipelines, APIs, and MLOps workflows You'll typically work in a small and cross-functional team. SKILLS AND EXPERIENCE The successful Machine Learning Engineer will have the following skills … Strong Python skills and experience with cloud platforms (AWS, GCP, or Azure) Experience building and deploying production ML systems Familiarity with Databricks, Spark, or MLOps workflows (nice to have but not essential) Solid understanding of modern ML methods and data engineering fundamentals Strong academic background (ideally Russell Group, with ...

into actionable AI roadmaps and solution designs. You will also guide implementation teams on best practices for prompt engineering, grounding strategies, RAG patterns, observability, MLOps, and Responsible AI-ensuring solutions are robust, compliant, and production ready. This role suits a hands on architect who can balance strategic vision with pragmatic … human in the loop review where needed. Ensure regulatory alignment (e.g., GDPR, ISO controls) and collaborate with risk, legal, and security for approvals. Define MLOps processes for versioning, evaluation, promotion, rollback, and monitoring (latency, cost, drift, hallucination rate, safety events). Instrument observability (logging, tracing, metrics) and error budgets; establish ...

clean energy transition? Have you deployed and scaled ML models on AWS in real-world environments? Are you ready to take ownership of MLOps in a fast-growing cleantech scale-up? A rapidly scaling London-based energy tech company is building an intelligent EV charging and energy optimisation platform used … industry partnerships to accelerate the shift to sustainable transport. The Data team is now expanding to support growing ML workloads. They’re hiring an MLOps Engineer to own and scale ML infrastructure across computer vision and broader DS/ML use cases. This role is critical to ensuring models ...

datasets Design annotation strategies, quality checks and evaluation frameworks from scratch Decide where data investment matters — and where it doesn’t (yet) ⚙️ Technical Direction & MLOps Establish pragmatic MLOps practices (CI/CD, deployment, monitoring, alerting) Build scalable but lightweight pipelines (AWS) Ensure models are robust, reliable, explainable where needed … core ML domain (strong preference for computer vision and/or generative AI) Experience with LLMs, conversational AI and evaluation of generative systems Strong MLOps and engineering mindset Hands-on with AWS, Python, SQL and modern ML tooling Strong data engineering and annotation strategy experience Experience leading teams and working ...

backtesting under realistic execution constraints. You know why naive train/test splits are dangerous in time series and what to do about it. MLOps & Productionisation. Experience taking models from notebook to production: experiment tracking (MLflow, W&B), model versioning, feature stores, drift detection, and retraining triggers. You can build … input into tooling choices: experiment tracking, feature stores, deployment infrastructure. We have strong engineering support and ship on AWS, but we're building the MLOps layer on the go and you'll help define it. We use AI coding tools - Cursor and Claude Code - as part of the daily workflow ...

Architect to lead the design, development, and operationalisation of advanced AI solutions. This is a hands-on, client-facing role spanning conversational AI, automation, MLOps/LLMOps, and AIOps, combining strategic architectural thinking with deep technical leadership to deliver scalable, secure, and high-impact AI capabilities across customer experience … production-ready architectures. You'll lead the development of Conversational AI implementations virtual agents, voice assistants, and multi-channel experiences, while implementing LLMOps and MLOps practices to manage the full model lifecycle from deployment through to performance optimisation. You'll design secure integrations using Model Context Protocol (MCP) and Agentic ...

ownership: Make decisions that move the whole company forward. We value autonomy, speed, and impact. Stack: Build with modern tools — Python, FastAPI, TypeScript, LLMs, MLOps What We’re Looking For 2+ years of software development experience Proven track record of building and shipping full-stack products in fast-paced, product … driven teams Hands-on experience building production AI systems with Python, PyTorch, and LLMs (OpenAI, Anthropic, etc.), integrated into real user workflows Familiarity with MLOps tools and CI/CD for both traditional and ML-driven systems Strong backend and API development skills - comfortable owning systems end-to-end, from ...

Intelligence Architect: Proven experience architecting solutions across Generative AI, Agentic AI, machine learning and automation Strong understanding of prompt engineering, RAG pipelines, model tuning, MLOps and LLMOps Experience delivering enterprise-scale RAG solutions using LLMs and vector databases Ability to design AI platforms that integrate with existing enterprise technology stacks … services Solid software engineering foundation for building scalable, maintainable AI systems Advanced Python expertise with AI and ML frameworks Experience with MLOps and LLMOps tooling including containerisation and orchestration platforms Proven experience delivering applications using state-of-the-art LLMs including prompt design, fine-tuning and evaluation Strong understanding ...

Senior Data Scientist London, hybrid 1 to 3 days per week. Competitive salary between £60,000 and £70,000 plus bonus and benefits. This is a rare opportunity to build a data science capability from ...

Define and execute the enterprise AI & automation roadmap Identify high-value use cases (personalisation, dynamic pricing, forecasting, workforce optimisation) Own AI/ML platforms, MLOps and LLM architecture (Azure preferred) Lead end-to-end delivery from experimentation to scaled deployment Build and lead a multi-disciplinary AI team Embed responsible … scale AI/ML and intelligent automation Strong hands-on knowledge of cloud AI platforms, data engineering and LLM/RAG architectures Experience implementing MLOps, observability and model governance Commercially minded, able to link AI outcomes to revenue, efficiency and customer impact Background within consumer-led/B2C environments ...

Join us at Entrust At Entrust, we’re shaping the future of identity centric security solutions. From our comprehensive portfolio of solutions to our flexible, global workplace, we empower careers, foster collaboration, and build solutions ...

About the Team : You'll be joining the team leading Entrust's Identity portfolio, formerly known as Onfido (an AI- powered digital identity solution). Our technology helps businesses verify real identities using machine learning ...

Senior System Engineer (AI/ML) | Permanent position Location: Central London Onsite: 5 days a week (South Kensington/Waterloo) Salary: Up to £82,500 + Excellent Benefits Available position: 2 positions Our client, an ...

About the Company: Our client is a leading global software platform transforming how modern organisations build, secure, and deliver software across DevOps, DevSecOps, and MLOps environments. Trusted by thousands of enterprises worldwide - including many of the world's largest organisations - their platform plays a mission-critical role in securing … security integrations SCA, SAST, SBOM management Container security Strong understanding of modern cloud and distributed systems Highly desirable: Background in software development Exposure to MLOps You must be equally credible in front of: Heads of DevOps Platform Engineering teams Security leaders C-level technical stakeholders Why This Role Stands ...

Captur helps software understand real world scenes in real-time with an SDK for flexible, on-demand visual recognition. We’re a small, rapidly scaling team backed by top-tier investors; we recently closed a ...

business. The Role * Lead end to end development of underwriting and acquisition models. * Set modelling standards, quality controls, and documentation practices. * Oversee deployment with MLops * Work closely with engineering, product, commercial, and data teams. Your Skills and Experience * Strong hands on experience building models in Python. * Background in credit risk … modelling, or customer behaviour modelling. * Confident communicator with senior stakeholders. * Leadership experience in technical teams. * Experience with XGBoost or other boosting techniques. * Knowledge of MLOps or R is a plus but not essential. What They Offer * £120,000 to £150,000 base salary. * Bonus * Share options. * Hybrid working, three days ...