76 to 100 of 123 MLOps Jobs in England

background) Experience building products from 0-1 , ideally in a startup or scale-up Comfortable working on APIs, cloud/infra products, or MLOps tooling Kubernetes An AI power user actively experimenting with multiple tools Confident individual contributor with strong stakeholder skills Strong experience in decentralised/blockchain environments Working ...

want to work with the latest in LLMs, co-pilots, agentic workflows, RAGs , and more, while also applying real data science, ML, and MLOps skills in live enterprise environments. What You’ll Do: Work directly with enterprise clients to design and deploy custom AI agents Tackle complex business problems with ...

services. AI & ML Leadership Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems. Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models. Evaluate and recommend emerging AI/ML technologies and platforms, driving innovation in intelligent … data governance, and quality frameworks. Implementing technical reviews and driving high standards. Collaborate with engineering and DevOps teams to establish CI/CD and MLOps architectures using Azure DevOps, Kubernetes, and Terraform. Guide the selection and implementation of visualization and analytics tools (Power BI, Tableau, PowerApps). Stakeholder Engagement: Engage ...

powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data MLOps & Infrastructure MLOps: Model versioning, monitoring, logging Bias Detection & Mitigation Content Filtering & Moderation Explainability & Transparency LLM Safety & Guardrails: Hallucination mitigation, prompt validation, safety layers Azure Cloud ...

personal to all of us.” – Julie Sweet, Accenture CEO. We are a dynamic team of specialists in Data Science, Data Engineering, and MLOps, dedicated to delivering cutting-edge AI solutions within secure government and defence environments. Join us to be part of an inclusive and collaborative environment where innovation thrives ...

personal to all of us.” – Julie Sweet, Accenture CEO. We are a dynamic team of specialists in Data Science, Data Engineering, and MLOps, dedicated to delivering cutting-edge AI solutions within secure government and defence environments. Join us to be part of an inclusive and collaborative environment where innovation thrives ...

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 ...

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 ...

using both classical ML and generative AI. Integrate AI into digital products through services, APIs, and safe, compliant guardrails. Manage model life cycle and MLOps while sharing best practices and enabling colleagues. Skills and Experience The successful AI Engineer will have the following skills and experience: Strong Python … experience, ideally with Databricks Experience with ML and LLM tools (e.g., scikit learn, XGBoost, PyTorch, TensorFlow, RAG, APIs) Comfortable with data engineering basics and MLOps practices Experience working with cloud platforms such as Azure, AWS, or GCP Benefits The successful Senior AI Engineer will receive the following benefits: Salary ...

software engineers to integrate models into production systems Evaluate, test, and improve model performance over time Contribute to data pipelines, model training workflows, and MLOps practices Stay up to date with the latest developments in AI, ML, and data science Document models, experiments, and technical decisions clearly Requirements Master … Have Experience with cloud platforms (AWS, Azure, or GCP) Familiarity with data engineering tools or SQL Exposure to deploying models into production or MLOps concepts Internship, research, or project experience in applied AI Working Arrangements Hybrid role : a mix of office-based work in Northampton and remote working Collaborative, supportive ...

solutions are secure, scalable, observable, and production-ready Technical Leadership & Innovation Lead and mentor teams of AI and software engineers Drive best practices across MLOps/LLMOps, governance, and AI observability Contribute to reusable accelerators, reference architectures, and go-to-market offerings What We’re Looking For: Essential Experience & Skills … experience architecting solutions across Generative AI, Agentic AI, ML, and automation Strong understanding of: Prompt engineering RAG pipelines Model fine-tuning (supervised/unsupervised) MLOps/LLMOps and AI observability Hands-on experience building enterprise RAG solutions using LLMs (e.g. OpenAI, Llama, Mistral, Claude) and vector databases (Pinecone, Weaviate, FAISS ...

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 click apply for full job details ...

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 ...

product and business stakeholders to shape AI use cases Ensure solutions meet security, governance and performance requirements Contribute to best practice around AI engineering, MLOps and deployment patterns Required Experience Proven experience as an AI Engineer/ML Engineer delivering AI into production Strong Python development skills Hands-on experience … architectures Comfortable working in agile, fast-moving delivery environments Nice to Have Experience with GenAI use cases (RAG, agents, copilots, document automation) Exposure to MLOps , CI/CD and monitoring of AI systems Experience in regulated or enterprise environments Consulting or client-facing delivery experience What's Attractive About This ...

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 ...

ML Engineer Location: Chester (Hybrid - 2x week in office) Salary: £70,000 - £80,000 About the Role I'm working with an established company who are looking to bring an ML Engineer into their team. ...

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 ...

pipelines Partner closely with data scientists and engineers to keep AI systems stable, efficient, and scalable What You Bring Strong background in AI Ops, MLOps, DevOps, or Infrastructure Engineering Hands-on experience with Linux, automation, scripting (Python/Bash) Experience with distributed systems and compute-heavy environments Familiarity with containers ...

strategic innovation and global partnerships. Role Description This is a full-time hybrid role based in the London Area, United Kingdom. As a Senior MLOps & Platform Engineer, you will be responsible for designing, building, and maintaining robust software infrastructure to support large-scale machine learning applications. You will troubleshoot technical … experience with database design, management, and optimization Familiarity with cloud platforms, DevOps practices, and CI/CD pipelines Experience working with AI or MLOps frameworks is a plus Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field Strong analytical thinking and ability to work ...

FastAPI , especially in serverless environments (e.g., Google App Engine) Streaming Data: Familiarity with real-time data pipelines and data ingestion at scale DevOps/MLOps: Exposure to Terraform , Docker , Kubernetes , and MLOps workflows What They Offer A chance to work on real-world data that impacts elite football performance Access ...

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 ...

constraints. Transitioning validated experiments into production-ready systems in collaboration with software and platform engineers. Building and maintaining ML pipelines on AWS using modern MLOps and LLMOps tooling. Implementing experiment tracking, model versioning, and reproducibility with full auditability. Supporting production models through monitoring, evaluation, and continuous improvement. Applying responsible … SageMaker, Lambda, and S3. Understanding of experiment design, evaluation techniques, and statistical reasoning. Experience taking models from experimentation into production environments. Familiarity with MLOps tooling such as MLflow, Weights & Biases, or Data Version Control. Experience developing or integrating LLM and GenAI applications, including prompt engineering and retrieval-augmented generation. Ability ...

Staff Machine Learning Engineer Salary - £100,000 Remote Europe Looking for a role that gives you the opportunity to lead impactful machine learning projects while shaping the technical direction of a growing AI function? Excited ...