1 to 25 of 58 Remote MLOps Jobs in the UK excluding London

or experimental Jupyter notebooks to full production deployment. Strong programming skills in Python, with familiarity in ML libraries/frameworks such as TensorFlow, PyTorch, and Scikit-learn. Experience with MLOps practices including model drift detection, decay, A/B testing, integration testing, differential testing, Python package building, and code version control. Skilled in data pipeline creation and working with both More ❯

SQL, NoSQL, and big data technologies (Spark, Hadoop, Snowflake, Databricks, etc.). Strong background in statistical modelling, probability theory, and mathematical optimization. Experience deploying machine learning models to production (MLOps, Docker, Kubernetes, etc.). Familiarity with AWS/GCP/Azure cloud ML platforms for scalable model training and inference. Strong problem-solving, communication, and business acumen skills. Experience in More ❯

and ability to communicate complex ideas clearly. Desirable Skills Experience with deep learning architectures (CNNs, RNNs, Transformers). Familiarity with cloud platforms (AWS, GCP, or Azure). Exposure to MLOps tools or pipeline automation. Previous internship or research experience in a related field. What’s on Offer Competitive graduate salary and benefits package. A collaborative, learning-focused environment. Opportunity to More ❯

LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor 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 ❯

Engineer Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that’s reinventing how the world designs More ❯

Engineer - AI for Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's reinventing how the world designs 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 ❯

products Ensure best practices in data engineering and contribute to architectural decisions Support senior team members in identifying and addressing data science opportunities. Required Skills & Experience Proven experience in MLOps or DevOps roles within machine learning environments Strong programming skills in Python, with hands-on experience in PySpark and SQL Deep understanding of ML lifecycle management and CI/CD More ❯

pragmatic mindset - able to balance innovation with execution. Nice-to-haves: Experience leading platform or DevOps product teams in life sciences, research, or AI-driven organisations . Familiarity with MLOps, GenAI, and large-scale compute orchestration . Background in computer science, engineering, or a related technical discipline. Package & Benefits: Base salary up to £145,000 . Car allowance , 18% bonus More ❯

marketing performance managers. Experience in Python and SQL. Experience with cloud platforms such as Amazon Web Services, Azure, or Google Cloud Platform. Deep understanding of Generative AI, NLP, and MLOps concepts. Analytical, flexible, independent, and a strong communicator. WE OFFER: A flexible, hybrid working policy (2 days from the office, depending on location). An excellent salary based on experience More ❯

Factory, GCP Dataflow and AWS services. Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance. Collaborate with DevOps teams to automate CI/CD and MLOps processes using Azure DevOps, Kubernetes, and Terraform. Visualize and communicate insights using Power BI, Tableau, and PowerApps. Mentor junior engineers and contribute to internal knowledge sharing. Ensure solutions meet security More ❯

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

MLOps Engineer Outside IR35 - 500-600 Per Day Ideally, 1 day per week/fortnight in the office, flexibility for remote work for the right candidate. A market-leading global e-commerce client is urgently seeking a Senior MLOps Lead to establish and drive operational excellence within their largest, most established data function (60+ engineers). This is a mission … critical role focused on scaling their core on-site advertising platform from daily batch processing to real-time capability. This role suits a hands-on MLOps expert who is capable of implementing new standards, automating deployment lifecycles, and mentoring a large engineering team on best practices. What you'll be doing: MLOps Strategy & Implementation: Design and deploy end-to-end … MLOps processes, focusing heavily on governance, reproducibility, and automation. Real-Time Pipeline Build: Architect and implement solutions to transition high-volume model serving (10M+ customers, 1.2M+ product variants) to real-time performance. MLflow & Databricks Mastery: Lead the optimal integration and use of MLflow for model registry, experiment tracking, and deployment within the Databricks platform. DevOps for ML: Build and automate More ❯

experience developing ML models, with a strong focus on medical imaging Proven track record using deep learning frameworks (PyTorch/TensorFlow) Solid Python skills and familiarity with cloud or MLOps tools (Docker, Kubernetes, MLFlow) Understanding of data pipelines and image analysis techniques (segmentation, registration, feature extraction) Benefits Share options and private healthcare Flexible hybrid working 28 days’ holiday + bank More ❯

Experience integrating AI models into production systems using GCP, AWS, or Azure. Familiarity with vector databases, embedding models, or retrieval-augmented generation (RAG). Knowledge of Docker, Airflow, or MLOps pipelines. Strong understanding of AI ethics, data privacy, and responsible model deployment. TO BE CONSIDERED... Please either apply online or email me directly at .By applying for this role, you More ❯

data privacy, handling of sensitive data (e.g. GDPR) and data lineage • Knowledge of the DataOps processes for the continuous deployment of UCDAs to production environments • Data Science machine learning (MLOps) model lifecycle • Worked with modern lakehouse and data management platforms – e.g.Databricks, Atlan, Monte Carlo What you’ll get in return: At easyJet, we pride ourselves on a vibrant and inclusive More ❯

data privacy, handling of sensitive data (e.g. GDPR) and data lineage Knowledge of the DataOps processes for the continuous deployment of UCDAs to production environments Data Science machine learning (MLOps) model lifecycle Worked with modern lakehouse and data management platforms – e.g.Databricks, Atlan, Monte Carlo What you'll get in return: At easyJet, we pride ourselves on a vibrant and inclusive More ❯

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 About the Company Our client is an extremely well know, digital marketplace focused on sustainable ecommerce. With over 35 million of active users globally, they’re redefining how people buy and sell second-hand fashion, aiming to make the future … The organisation champions diversity, equal opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work-life balance. The role of Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 Our Client is looking for an experienced MLOps Engineering Manager to lead and … scale their MLOps function. You will be shaping how machine learning is developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real More ❯

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 About the Company Our client is an extremely well know, digital marketplace focused on sustainable ecommerce. With over 35 million of active users globally, they’re redefining how people buy and sell second-hand fashion, aiming to make the future … The organisation champions diversity, equal opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work-life balance. The role of Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 Our Client is looking for an experienced MLOps Engineering Manager to lead and … scale their MLOps function. You will be shaping how machine learning is developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real More ❯