1 to 25 of 96 MLOps Jobs in the UK excluding London

Bedrock, etc.). Desired: Experience deploying models as APIs/microservices in cloud-native environments. Familiarity with prompt tuning, embedding generation, vector search, and knowledge retrieval frameworks. Understanding of MLOps best practices, version control, CI/CD pipelines, and containerization (Docker, Kubernetes). Prior experience working with GenAI tools and response-augmented generation workflows. Education: Bachelor's or Master's More ❯

environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What We Offer Fully remote working A More ❯

60k per annum As a Machine Learning Engineer , you will be part of an MLOps team, working alongside data scientists, software engineers, and other stakeholders to bring machine learning models to life. You will be responsible for deploying, maintaining, and monitoring models in production, improving model performance, and refining the machine learning infrastructure to support business objectives. Your role will More ❯

real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially More ❯

environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯

environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯

environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯

the ability to balance research innovation and commercial value delivery. Comfortable operating across cloud environments (GCP, Azure, AWS) and deploying AI/ML systems at scale. Strong knowledge of MLOps practices and infrastructure including CI/CD, model versioning, orchestration, and monitoring. A collaborative and inspiring leader who brings out the best in technical teams and communicates complex concepts to More ❯

and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow More ❯

and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow More ❯

with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯

experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Solid understanding of machine learning algorithms and statistical methods Experience working with cloud platforms (AWS, GCP, or Azure) Familiarity with MLOps tools and practices is a plus A degree in Computer Science, Engineering, Mathematics, or a related field What We Offer Salary: £50,000–£60,000 depending on experience Hybrid working More ❯

and eagerness to stay ahead of the curve Desirable Skills Background in agile and collaborative project delivery Familiarity with data visualisation tools (e.g. Tableau) Exposure to model monitoring and MLOps practices MSc or equivalent in a quantitative discipline (e.g. Data Science, Statistics, Computer Science) *Rates depend on experience and client requirements More ❯

Physics, or related fields 4+ years Systems Engineering or related experience 2+ years experience with CV, NLP, and LLM architectures Knowledge of large-scale software architectural patterns Experience with MLOps, automation tools, containerization (Docker, Kubernetes), and ML lifecycle management Knowledge of Rust is a plus Experience with fine-tuning GenAI models and Reinforcement Learning is a plus Customer focus and More ❯

with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯

methods? Any experience of popular known deployment methods on k8s cluster? Gitops/Git/Jenkins Any experience using gitops pipeline? Nice to have Understanding of LLM Evaluation Frameworks MLOps platforms or LLMOps background Understanding of AI Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all candidates More ❯

or cloud platforms like AWS, Lambda, Azure Strong problem-solving skills and critical thinking in AI research Strategic planning abilities Additional Skills (desired): Experience with protein or DNA bioinformatics MLOps expertise Software engineering skills, data pipelining (e.g., Airflow), cloud deployment experience Knowledge of Agile methodologies Interested in joining as our Head of AI? We look forward to hearing from you More ❯

working in B2C, e-commerce, subscription, retail, or fintech industries is a strong advantage Nice to Have Experience with NLP for customer feedback or support ticket analysis Exposure to MLOps for model deployment and monitoring Familiarity with tools like Amplitude, Mixpanel, or Google Analytics Why Join Us? Shape data-driven strategy for how we understand and engage with our customers More ❯

CI/CD pipelines. Experience writing clean, efficient, and modular code suitable for production environments. Desirable Skills or Knowledge Familiarity with AMO physics or quantum machine learning. Experience with MLOps best practices. Knowledge of systems like Apache Kafka, MQTT or real-time data pipelines. Experience with cloud platforms (AWS, Azure, GCP). Deep expertise in time series modelling techniques (e.g. More ❯

or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability More ❯

or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability More ❯

or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability More ❯

Edinburgh, United Kingdom Posted on 01/07/2025 Are you a DevOps engineer ready to dive into the world of MLOps? Do you want to work on real-world deployments of cutting-edge machine learning models, including Large Language Models (LLMs)? We're looking for a motivated Junior MLOps Engineer with a DevOps background, eager to help us … deploy and maintain machine learning models, especially Large Language Models (LLMs), in production environments. If you have solid DevOps experience and are keen to grow your MLOps skills, we'd love to hear from you! About Aveni Aveni is an award-winning technology company. We use advanced AI to enable scalable efficiency for financial services companies, combining world-leading Natural … CD for ML pipelines Developing production-grade APIs (REST/gRPC) to serve models Collaborating with engineers, data scientists & DevOps teams Requirements Your Experience Industry experience in DevOps or MLOps roles (ideally in AWS environments) Hands-on with Docker, Kubernetes, and Terraform Strong scripting skills in Python or Bash Familiar with ML lifecycle tools, model monitoring, and versioning Exposure to More ❯

a plus) Strong Python, SQL, and data science toolkit experience Proven track record in deploying end-to-end ML solutions in cloud environments (AWS, Azure, or GCP) Familiarity with MLOps Excellent communication skills and ability to work cross-functionally This is a fantastic opportunity to deliver impactful work in a collaborative and forward-thinking environment. Location: Remote first - 1 day More ❯

scaling data systems in cloud environments (Azure preferred; AWS/GCP also welcome) Strong Python and SQL skills with deep knowledge of modern data tooling and pipelines Experience with MLOps, CI/CD workflows, containerisation (e.g., Docker, Kubernetes) and production-grade APIs Understanding of data governance, privacy and regulatory compliance (e.g., GDPR) Nice to have: Familiarity with Infrastructure as Code More ❯