351 to 375 of 414 MLOps Jobs in the UK

reliability, and scalability. Participate in internal ML community, influencing how we implement AI and computer vision technologies. Take ownership of customer outcomes and contribute across software engineering, DevOps, and MLOps functions. About You We’re looking for a proactive and versatile engineer who thrives in a collaborative environment and enjoys solving meaningful technical challenges. You’ll be comfortable engaging with … typically three times per year). Nice to Have: Experience working in a fully remote, international team. Previous startup experience. Experience building or operating agentic AI systems. Familiarity with MLOps practices and tools, CI/CD pipelines (e.g. GitLab CI, Argo CD), and infrastructure-as-code tools (e.g. Terraform). Knowledge of SQL/NoSQL databases , Kubernetes , and LLMs (Large More ❯

Contract Python Engineers – Legal AI Outside IR35 £400-£650 (DOE) 6 months+ 1 day onsite (Cambridge or London) Innovare is the exclusive recruitment partner for a Legal-AI pioneer that’s redefining how contracts are reviewed, using a proprietary AI More ❯

A global lifestyle brand is hiring a Data Science Manager to lead personalisation efforts within its CRM ecosystem. The role sits in the Consumer Intelligence and Experience (CIX) team, which drives customer engagement through predictive analytics and insights across all More ❯

A global lifestyle brand is hiring a Data Science Manager to lead personalisation efforts within its CRM ecosystem. The role sits in the Consumer Intelligence and Experience (CIX) team, which drives customer engagement through predictive analytics and insights across all More ❯

Overview A global lifestyle brand is hiring a Data Science Manager to lead personalisation efforts within its CRM ecosystem. The role sits in the Consumer Intelligence and Experience (CIX) team, which drives customer engagement through predictive analytics and insights across More ❯

data pipelines and data infrastructure. The work involves creating reliable, secure and scalable data flows that support analytics and AI teams. You’ll collaborate with Data Engineering, AI and MLOps teams to ensure data is structured, standardised and ready for downstream use. What you’ll work on Designing and managing ETL/ELT pipelines. Building and maintaining data architectures (data … to improve reliability and performance. Building transformation frameworks for data preparation. Implementing validation, monitoring and observability for data quality. Supporting privacy, security and compliance standards. Working with AI/MLOps teams to support model training and reproducible data pipelines. Applying DataOps practices including CI/CD for data workflows. Required experience Experience as a Data Engineer in production environments. Strong … Ability to build validation, monitoring and quality control systems. Experience designing scalable data solutions for large datasets. Preferred experience Working with regulated or sensitive datasets. Integrating data workflows with MLOps pipelines. Knowledge of anonymisation, pseudonymisation, or synthetic data. Experience with automated alerting and drift detection. Experience mentoring or contributing to engineering standards. Benefits Fully remote working with team collaboration days More ❯

Role As our first senior AI hire, you’ll take ownership of designing and building the foundation of our AI ecosystem. You’ll shape the infrastructure strategy, establish our MLOps pipelines, and work closely with product and data teams to enable seamless model development and deployment. Once the environment is established, you’ll play a key role in recruiting and … mentoring two mid-level AI engineers who will join your team. Responsibilities Architect, build, and maintain an in-house AI environment (on-prem or hybrid cloud). Design MLOps workflows for training, deploying, and monitoring models. Integrate and manage containerized AI engines (Docker/Kubernetes). Establish best practices for model versioning, data pipelines, and reproducibility. Collaborate with ML and … or on-premise platforms (non-cloud environments). Solid understanding of data pipelines, APIs, and scalable system architecture. Preferred Experience leading small teams or mentoring other engineers. Familiarity with MLOps tools and best practices. Background in integrating AI solutions into enterprise products. Awareness of privacy, bias mitigation, and model explainability techniques. What We Offer Opportunity to design and own the More ❯

Role As our first senior AI hire, you’ll take ownership of designing and building the foundation of our AI ecosystem. You’ll shape the infrastructure strategy, establish our MLOps pipelines, and work closely with product and data teams to enable seamless model development and deployment. Once the environment is established, you’ll play a key role in recruiting and … mentoring two mid-level AI engineers who will join your team. Responsibilities Architect, build, and maintain an in-house AI environment (on-prem or hybrid cloud). Design MLOps workflows for training, deploying, and monitoring models. Integrate and manage containerized AI engines (Docker/Kubernetes). Establish best practices for model versioning, data pipelines, and reproducibility. Collaborate with ML and … or on-premise platforms (non-cloud environments). Solid understanding of data pipelines, APIs, and scalable system architecture. Preferred Experience leading small teams or mentoring other engineers. Familiarity with MLOps tools and best practices. Background in integrating AI solutions into enterprise products. Awareness of privacy, bias mitigation, and model explainability techniques. What We Offer Opportunity to design and own the More ❯

LLMs. You will work across research and implementation, taking models from concept to production, setting technical standards and supporting junior engineers. The role involves close collaboration with the AI, MLOps and Data Engineering teams, contributing to the wider technical strategy and ensuring models are reliable, maintainable and scalable. Key Responsibilities Design and develop NLP and LLM-based systems for internal … models using domain-specific datasets. Carry out analysis to understand model behaviour, drift and explainability. Build and maintain tools for evaluation, prompt testing and dataset preparation. Work with the MLOps engineer to deploy, monitor and retrain models in production. Support CI/CD processes for AI, including version control, reproducibility and rollback workflows. Provide mentorship and guidance to junior engineers. … into production systems. Familiarity with retraining workflows and performance monitoring. Understanding of explainability and fairness techniques. Hands-on experience with containerisation and orchestration (Docker/Kubernetes). Understanding of MLOps practices, CI/CD and model registry processes. Experience mentoring or guiding junior engineers or leading technical initiatives. Nice to Have Experience working with sensitive or regulated data (not essential More ❯

. Develop pipeline programming using Python, Spark, and SQL; integrate APIs for seamless workflows. Support Machine Learning and AI initiatives, including NLP, Computer Vision, Time Series, and LLMs. Implement MLOps, CI/CD pipelines, data testing, and quality frameworks. Act as an AI super-user, applying prompt engineering and creating AI artifacts. Work independently while providing clear justification for technical … Proficient with cloud platforms (Snowflake, AWS fundamentals). Solid understanding of data architecture, warehousing, and modeling. Programming expertise: Python, Spark, SQL, API integration. Knowledge of ML/AI frameworks, MLOps, and advanced analytics concepts. Experience with CI/CD, data testing frameworks, and versioning strategies. Ability to work effectively in multi-team, vendor-integrated environments. Why This Role Join a More ❯

. Develop pipeline programming using Python, Spark, and SQL; integrate APIs for seamless workflows. Support Machine Learning and AI initiatives, including NLP, Computer Vision, Time Series, and LLMs. Implement MLOps, CI/CD pipelines, data testing, and quality frameworks. Act as an AI super-user, applying prompt engineering and creating AI artifacts. Work independently while providing clear justification for technical … Proficient with cloud platforms (Snowflake, AWS fundamentals). Solid understanding of data architecture, warehousing, and modeling. Programming expertise: Python, Spark, SQL, API integration. Knowledge of ML/AI frameworks, MLOps, and advanced analytics concepts. Experience with CI/CD, data testing frameworks, and versioning strategies. Ability to work effectively in multi-team, vendor-integrated environments. Why This Role Join a More ❯

🔍 ML Ops Engineer – Cloud, Data, and AI Are you passionate about shaping the future of data and cloud technology? We’re partnering with a forward-thinking financial organization investing heavily in its data and AI capabilities — and they’re looking More ❯

🔍 ML Ops Engineer – Cloud, Data, and AI Are you passionate about shaping the future of data and cloud technology? We’re partnering with a forward-thinking financial organization investing heavily in its data and AI capabilities — and they’re looking More ❯

Overview You'll be part of a collaborative, entrepreneurial environment that values innovation, excellence, and thought leadership. This is more than a sales-adjacent role - it's your opportunity to shape the future of data & AI consulting and lead from More ❯

ML Ops Engineer (AWS/Terraform) Location: Remote Engagement: Permanent or Contract About the Role We’re looking for an experienced ML Ops Engineer to help scale the deployment and management of multiple AI models across AWS. You’ll be More ❯

Designation Senior Principal Analyst Function Sales Enablement Experience 5-10 years Location United Kingdom - Edinburgh, London, Manchester Skills AI, Machine Learning, Solution Architecture You'll be part of a collaborative, entrepreneurial environment that values innovation, excellence, and thought leadership. This More ❯

Designation Senior Principal Analyst Function Sales Enablement Experience 5-10 years Location United Kingdom - Edinburgh, London, Manchester Skills AI, Machine Learning, Solution Architecture You'll be part of a collaborative, entrepreneurial environment that values innovation, excellence, and thought leadership. This More ❯

Designation Senior Principal Analyst Function Sales Enablement Experience 5-10 years Location United Kingdom - Edinburgh, London, Manchester Skills AI, Machine Learning, Solution Architecture You'll be part of a collaborative, entrepreneurial environment that values innovation, excellence, and thought leadership. This More ❯

Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image More ❯

MLOps Engineer Contract London based (hybrid or onsite depending on preference) Outside IR35 £600 to £650 per day I am supporting a client in London who is preparing to scale their machine learning capability. They need an experienced MLOps Engineer who can take models from development into a reliable production environment and keep everything running smoothly throughout the lifecycle. What … stability and performance across the ML platform. Key skills • Strong Python for production environments. • Solid experience with Azure for ML workloads including compute, networking and storage. • Good knowledge of MLOps tools such as MLflow, Azure ML, Kubeflow or similar. • Strong background in CI and CD using GitHub Actions, Azure DevOps or similar. • Experience working in containerised environments using Docker and … have • Experience working on large scale data or ML projects. • Good understanding of data engineering fundamentals. • Experience working in regulated or high availability environments. If you're an experienced MLOps Engineer feel free to apply or send your C.V to nokakpu@revoco-talent.co.uk MLOps Engineer More ❯

MLOps Engineer Contract London based (hybrid or onsite depending on preference) Outside IR35 £600 to £650 per day I am supporting a client in London who is preparing to scale their machine learning capability. They need an experienced MLOps Engineer who can take models from development into a reliable production environment and keep everything running smoothly throughout the lifecycle. What … stability and performance across the ML platform. Key skills • Strong Python for production environments. • Solid experience with Azure for ML workloads including compute, networking and storage. • Good knowledge of MLOps tools such as MLflow, Azure ML, Kubeflow or similar. • Strong background in CI and CD using GitHub Actions, Azure DevOps or similar. • Experience working in containerised environments using Docker and … have • Experience working on large scale data or ML projects. • Good understanding of data engineering fundamentals. • Experience working in regulated or high availability environments. If you're an experienced MLOps Engineer feel free to apply or send your C.V to nokakpu@revoco-talent.co.uk MLOps Engineer More ❯

customers by feeding into the delivery of strategic data science solutions whilst setting up resilient and future-proof ML infrastructure and engineering foundations. Designing and developing our ML Operations (MLOps) infrastructure and practices to support the effective transition of machine learning models and PoCs into production in a cost and operationally efficient manner. Monitoring, and maintaining the health of new … deployment; Working with business stakeholders to proactively raise awareness of any risks to the model(s) outputs and/or their interpretation, and usability. Implementing modern code development and MLOps strategies, in collaboration with Data Science and Data Engineering to support the proactive identification, targeting and resolution of any ML model(s) performance issues across their entire lifecycle. Developing operating … with third party partners and software providers to improve, implement and/or support the move to production of novel Machine Learning solutions. Raising awareness of best practices for MLOps; collaborating and knowledge sharing with individuals across the data and software teams, and wider business. Collaborating with Data Science, Data Engineering and Software Engineering teams to drive cross-function visibility More ❯

Solutions Architect - DevOps/DevSecOps/MLOps Solutions Architect UNITED KINGDOM DevOps Presales Engineer - LONDON - UNITED KINGDOM Salary: £160,000 (80/20 split) Remote Status: Hybrid - 3 days/week in LONDON office Job Description: We are looking for a DevOps Presales Engineer for our client, a market leader in DevOps, DevSecOps, and MLOps.This is a company trusted by … at industry events and conferences Train customers and community members on product capabilities Feed frontline insights back to the company to shape the product roadmap Stay ahead of DevOps & MLOps trends and bring that expertise to every customer conversation This is not a back-office DevOps role. You'll be front and centre in the sales process - a trusted technical More ❯

powered solutions . Lead on data strategy , from collection and simulation to training and validation. Ensure AI safety, ethics, explainability , and compliance with defence standards. Define best practices in MLOps , model evaluation, and continuous integration. Essential Skills & Experience MSc (or PhD) in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or related engineering field . 5+ years of experience in AI … or sensor fusion . Excellent communication and problem-solving skills. Desirable Extras Publications in leading AI/ML or robotics conferences (e.g. NeurIPS, CVPR, ICLR, ICRA). Experience with MLOps pipelines, synthetic data, and model optimisation for edge devices . Understanding of sensor fusion, perception pipelines , and AI safety principles . What’s on Offer Highly competitive base salary. Generous More ❯

powered solutions . Lead on data strategy , from collection and simulation to training and validation. Ensure AI safety, ethics, explainability , and compliance with defence standards. Define best practices in MLOps , model evaluation, and continuous integration. Essential Skills & Experience MSc (or PhD) in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or related engineering field . 5+ years of experience in AI … or sensor fusion . Excellent communication and problem-solving skills. Desirable Extras Publications in leading AI/ML or robotics conferences (e.g. NeurIPS, CVPR, ICLR, ICRA). Experience with MLOps pipelines, synthetic data, and model optimisation for edge devices . Understanding of sensor fusion, perception pipelines , and AI safety principles . What’s on Offer Highly competitive base salary. Generous More ❯