151 to 175 of 346 MLOps Jobs in England

deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to validate impact Act as a technical lead within project teams, mentoring mid-level More ❯

deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to validate impact Act as a technical lead within project teams, mentoring mid-level More ❯

systems. Technical Leadership : Proven experience in scaling AI products, DevOps, and cloud architecture. Backend & Data Proficiency : Skilled in Python, Node.js, PostgreSQL, MongoDB, and API security. AI Deployment : Familiarity with MLOps, data engineering, and ethical AI practices. Strategic Thinking : Ability to align tech strategy with business objectives and cost efficiency. Security & Compliance : Strong understanding of GDPR, API authentication, and observability. Big More ❯

systems. Technical Leadership : Proven experience in scaling AI products, DevOps, and cloud architecture. Backend & Data Proficiency : Skilled in Python, Node.js, PostgreSQL, MongoDB, and API security. AI Deployment : Familiarity with MLOps, data engineering, and ethical AI practices. Strategic Thinking : Ability to align tech strategy with business objectives and cost efficiency. Security & Compliance : Strong understanding of GDPR, API authentication, and observability. Big More ❯

reviews, observability and performance profiling. - ️ Experience using multi modal AI (document layout, vision language models, building agents). - Experience building quick prototypes (e.g. Streamlit, Dash) to validate ideas rapidly. - MLOps tooling (e.g. MLflow) and model monitoring experience. - Strong communication skills and action oriented. Nice to Have - ️ Hands on with Azure services (Storage, Container Registry, OpenAI Services). - Demonstrated experience building More ❯

knowledge as a plus. Demonstrated experience building APIs supporting analytics, research, or actuarial functions in an insurance environment. Proficiency with cloud technologies such as Snowflake, Databricks, and familiarity with MLOps frameworks. Exhibit strong collaboration, problem-solving, and communication skills, with the ability to adapt to changing priorities and simplify complex problems. Seniority level Seniority level Mid-Senior level Employment type More ❯

experience with molecular or protein visualisation . You've built UIs visualising molecules or proteins using Mol You are passionate about model serving . You have some familiarity with MLOps and ML serving. Your responsibilities Develop and own both front-end and back-end components of our platform. Craft the most graphically delightful web experiences around proteins. Optimise the performance More ❯

Lake, Azure Functions, Power BI. Experience in project delivery and consultancy. Prince 2 Agile or similar. Experience in Blue Light, NHS, Local Government or Social Housing sectors. Experience with MLOps workflows and frameworks. The successful candidate will be required to obtain Security Clearance and NPPV Level 3. More ❯

out as these open up. What You'll Be Doing As a Senior Machine Learning Engineer at Faculty, you'll design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. You'll be engineering-focused, with a keen interest and working knowledge of operationalised machine learning. You have a desire to take cutting-edge ML More ❯

a cloud environment (preferably Azure). Strong hands-on development skills. Our main application stack is based on .Net and C# Deep understanding of machine learning, data pipelines, and MLOps practices. Experience with Azure services such as Azure Machine Learning, Azure Data Factory, Azure Synapse, and Azure Functions. Implementing modern retrieval techniques such as vector search, semantic search and Retrieval More ❯

you will design and develop scalable, cloud-based backend systems using multiple programming languages. You'll contribute to QA, automation, and infrastructure management while supporting DevOps and AI/MLOps practices. Collaboration on architecture, environment lifecycle, and regulatory compliance is key. As Full Stack Software Engineer, you will have to : Develop scalable software systems for back-end that will be More ❯

of language models and transformers Rich understanding of vector stores and search algorithms Large-scale ETL development Direct engineering experience of high performance, large-scale ML systems Hands on MLOps experience, with an appreciation of the end-to-end CI/CD process Have experience supporting fast-paced startup engineering teams A contributor to opensource and always thinking out of More ❯

/implementation/consulting experience of distributed applications - 7+ years management of technical, customer facing resources - 7+ years of design/implementation of production AI/ML systems and MLOps pipelines with hands-on experience with state-of-the-art data and ML frameworks (PyTorch, HuggingFace, Spark, Langchain), technical familiarity with LLMs/FMs, RAG, and prompt engineering techniques. PREFERRED More ❯

practices Track record of leveraging data insights to inform product strategies, ideally with experience in product analytics Knowledge of machine learning frameworks or AI-based products, as well as MLOps best practices(nice to have) Excellent communication and stakeholder management skills, with the ability to concisely report technical information to both technical and non-technical audiences What we offer Diverse More ❯

the buildout of scientific applications and scientific data management applications Building a state-of-the-art platform for conducting ML research with a high velocity and reliability Building key MLOps components for transferring models from research to production at scale Working on low-level performance optimization to increase the efficiency and performance of ML models and infrastructure Optimizing and maximally More ❯

the buildout of scientific applications and scientific data management applications Building a state-of-the-art platform for conducting ML research with a high velocity and reliability Building key MLOps components for transferring models from research to production at scale Working on low-level performance optimization to increase the efficiency and performance of ML models and infrastructure Optimizing and maximally More ❯

Date: July 2025 Company: Fuzzy Labs Job Title: Lead MLOps Engineer Location: Central Manchester Working style: Hybrid Fuzzy Labs are a Manchester based startup that helps our clients productionise machine learning through Open Source MLOps. We exist to help harness and channel the power of AI more quickly, to make positive change and use AI for good. We are growing … our team of engineers to help deliver an increasing number of client projects. You won't need an existing MLOps background to apply for this role. You'll learn as you go by immersing yourself in this exciting new field. What we're looking for We've seen considerable growth over the past few years and this will continue as … we build on our reputation as Open Source MLOps experts, while working with the community, and delivering solutions to our clients. The ideal candidate would be motivated to grow and progress in line with the company's ambitions. As well as being a great engineer, motivated by the chance to be at the forefront of MLOps adoption, you'll also More ❯

Who are we? Our mission is to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. More ❯

MLOps Engineer London £60,000-£70,000 About the Role: Join a cutting-edge technology company at the forefront of immersive experiences powered by machine learning and extended reality. We are seeking a skilled MLOps Engineer to help build, deploy, and maintain scalable machine learning infrastructure that drives innovation in our products. You will play a critical role in developing … scalable ML infrastructure that powers immersive XR applications with real-time 3D content. Key Responsibilities: Design, develop, and maintain scalable MLOps pipelines tailored for XR applications, ensuring smooth deployment and monitoring of machine learning models. Collaborate closely with 3D artists and XR developers to integrate machine learning workflows with 3D rendering engines. Optimize ML models and workflows for real-time … related to ML inference and 3D rendering workloads. Develop monitoring solutions to track model performance and system health in production. Stay up to date with the latest trends in MLOps, XR technologies, and 3D rendering techniques to propose innovative improvements. Qualifications: Proven experience as an MLOps engineer or similar role with a focus on 3D applications Strong programming skills in More ❯

best practices to protect data and infrastructure. Please speak to us if you have .. ..the following professional aspirations Deepening Technical Expertise : Aspire to deepen your technical expertise in MLOps practices and master tools and technologies related to cloud platforms, containerisation, and automation. Career Advancement : Aim to progress to a senior MLOps engineer position or potentially transition into a technical … effectively. Mentorship Opportunities : Show interest in mentoring junior engineers and contributing to a collaborative team culture that creates growth and knowledge sharing. Aligning with Business Goals : Aim to align MLOps initiatives with business objectives, ensuring that the ML infrastructure supports the companys strategic direction and contributes to overall success. Exploring Innovative Solutions : Be eager to explore and implement innovative data … data ingestion, storage, and management is essential. Monitoring and Logging Tools : Experience with monitoring and logging tools to track system performance and model effectiveness in production environments. Familiarity with MLOps Tools: Knowledge of various MLOps tools and platforms, including MLflow, Databricks, Kubeflow, and SageMaker, to streamline the machine learning lifecycle. Version Control Systems: Proficient in using version control systems such More ❯

and 2023) and most excitingly, Media Week's Agency of the Year 2023! Job Description What will you be doing? This role presents an opportunity to engage deeply with MLOps, vector databases, and Retrieval-Augmented Generation (RAG) pipelines - skills that are in incredibly high demand. If you are passionate about shaping the future of AI and thrive on complex, high … Pinecone, Milvus, Chroma) for embedding storage and retrieval. Generative AI Familiarity: Understanding of data paradigms for LLMs, RAG architectures, and how data pipelines support fine-tuning or pre-training. MLOps Principles: Familiarity with MLOps best practices for deploying and managing ML models in production. Data Governance & Ethics: Experience implementing data governance frameworks, ensuring data quality, privacy, and compliance, with an More ❯

network you want to login/join with: Solutions Architect London, UK | Solutions Engineering Share position *Residency in London Area is required At JFrog, were reinventing DevOps, DevSecOps and MLOps to help the worlds greatest companies innovate, develop faster and be more secure -- and we want you along for the ride. This is a special place with a unique combination More ❯

memory graphs) and graph neural networks for reasoning. Strong grounding in probabilistic models , causal inference , and AI reasoning approaches. Hands-on experience with cloud platforms (AWS, GCP, Azure) and MLOps workflows. Solid understanding of vector databases (e.g. Pinecone, Weaviate, Milvus) and retrieval-augmented generation (RAG) techniques. Comfort with rapid technical recall for industry benchmarks, model parameters, and framework capabilities. More ❯

memory graphs) and graph neural networks for reasoning. Strong grounding in probabilistic models , causal inference , and AI reasoning approaches. Hands-on experience with cloud platforms (AWS, GCP, Azure) and MLOps workflows. Solid understanding of vector databases (e.g. Pinecone, Weaviate, Milvus) and retrieval-augmented generation (RAG) techniques. Comfort with rapid technical recall for industry benchmarks, model parameters, and framework capabilities. More ❯

frameworks such as PyTorch or TensorFlow. Familiarity with FDA regulatory pathways for medical software (e.g., 510(k), De Novo), and standards like IEC 62304 or ISO 13485. Experience with MLOps practices and model versioning in compliant environments. Preferred Qualifications: Experience building ML models with wearable data (e.g., continuous heart rate, motion, respiration). Exposure to embedded AI or edge model More ❯