18 of 18 MLOps Jobs in the North West

with AI/ML workflows or deploying machine learning models in production. Knowledge of big data technologies like Hadoop, Hive, or Spark. Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or DataRobot. Education: Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience More ❯

agile working environment, with a focus on iterative and collaborative project delivery. Have worked with data visualisation tools e.g. Tableau. Experience in model monitoring. (MLOPS experience would be desirable.) Have gained a master's in a quantitative field such as Computer Science, Statistics or related disciplines. Recruitment Process: Pre-screen More ❯

. Skills we'd also like to hear about: Evidence of modelling experience applied to industry relevant use cases. Familiarity with working in an MLOps environment. Familiarity with simulation techniques. Familiarity with optimisation techniques. What you'll receive from us: No matter where you may be in your career or More ❯

Strong proficiency in Python and SQL. Hands-on experience with Power BI or similar data visualisation tools. familiarity with version control (e.g., Git) and MLOps principles. Great communication skills both verbally and written. The role is offering a salary of up to £50,000 per annum and comes with a More ❯

growth-focused role perfect for someone with a solid technical foundation and a hunger to dive deep into the evolving world of Generative AI, MLOps, and cloud infrastructure. We value in-person collaboration here at Matillion, therefore this role will follow our hybrid work structure where employees work 2 days More ❯

comprehensive model monitoring. Develop model training and evaluation pipelines to accelerate model development/deployment adhering to software development best practices (CI/CD & MLOps) Engage with Engineering teams to ensure we capture data points that are relevant and useful for insights and modelling. Requirements You have at least More ❯

Solid understanding of event-driven architecture Experience with CI/CD practices and tools Familiarity with microservices and modern cloud-based platforms Exposure to MLOps and Kubernetes is a big plus Computer Science degree or equivalent practical experience More ❯

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 enjoy being part of a culture that values: Loving what we do: a real passion for Open Source, MLOps and taking pride in great work. More ❯

MLOps Engineers (Mid, Senior & Lead level) – UKIC DV Cleared | AI/ML Start-up | Manchester | Hybrid Are you an MLOps Engineer with active UKIC DV clearance looking to make a real-world impact at the cutting edge of AI and machine learning? We’re hiring Mid, Senior, and Lead MLOps … play a key role in designing and deploying robust ML infrastructure, supporting both public and private sector clients. What You'll Do as an MLOps Engineer: Deploy and manage machine learning models in production environments Build and optimise scalable MLOps pipelines using modern tools and cloud platforms (AWS, Azure, GCP … world AI/ML projects that truly make a difference Contribute ideas in a relaxed, open, and innovation-driven culture Location & Flexibility for the MLOps Engineer: Hybrid role based in Manchester Strong work-life balance and a genuinely fun, inclusive environment Excellent career progression , bonus structure What We're Looking More ❯

modelling techniques Experience of leading delivery of the end-to-end lifecycle of AI models, including development, deployment, monitoring, and maintenance, including knowledge of MLOps practices An understanding of ethical consideration in AI, with the ability to role model their importance with business partners Knowledge of banking data architecture and More ❯

and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally … as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data More ❯

and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally … as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data More ❯

through to deployment. Responsibilities: Develop and deploy scalable machine learning models into production environments Build and maintain robust ML pipelines using modern cloud and MLOps tooling Collaborate with data scientists, engineers, and stakeholders to deliver end-to-end solutions Implement testing, monitoring, and performance optimisation of ML systems Contribute to … learning models to production Strong programming skills in Python and familiarity with modern ML frameworks Experience working in cloud environments (preferably AWS) Understanding of MLOps practices and tooling Effective communication and ability to work independently in a remote team Desirable: Experience with LLMs or generative AI technologies Previous consultancy or More ❯

through to deployment. Responsibilities: Develop and deploy scalable machine learning models into production environments Build and maintain robust ML pipelines using modern cloud and MLOps tooling Collaborate with data scientists, engineers, and stakeholders to deliver end-to-end solutions Implement testing, monitoring, and performance optimisation of ML systems Contribute to … learning models to production Strong programming skills in Python and familiarity with modern ML frameworks Experience working in cloud environments (preferably AWS) Understanding of MLOps practices and tooling Effective communication and ability to work independently in a remote team Desirable: Experience with LLMs or generative AI technologies Previous consultancy or More ❯

At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges More ❯

and microservices to serve AI models at scale. Integrate behavioural intelligence models across cloud platforms (AWS, GCP, Azure). Set up end-to-end MLOps pipelines: monitoring, retraining, and automation. Collaborate with cross-functional teams to align tech with user-centric product design. What We’re Looking For: 2+ years … components. Proficiency in Python and frameworks like PyTorch/TensorFlow, Scikit-learn. Experience deploying models with Docker, Kubernetes, or serverless architectures. Solid grasp of MLOps workflows, versioning, and cloud automation. Strong foundations in algorithms, data structures, and system design. Bonus: Familiarity with behavioural biometrics, sensor-based or time series data More ❯

you Drive the evolution of our data platforms by shaping the design, deployment and ongoing support of our tooling/capabilities for data streaming, MLOps, and batch- and real-time analytics Focus on what matters: whether its reducing time to first insight for our internal customers, or proactively reducing the … have any of the following experiences too; Deep familiarity with modelling approaches for cloud data lakehouses/medallion architectures Building, extending or extensively using MLOps frameworks (open-source or otherwise), particularly for applications in support of customer personalisation Surfacing analytical products into data visualisation platforms (we use PowerBI) via semantic More ❯

Attend client facing meetings, explaining the solutions on offer. Use SQL to extract, clean, and transform data from complex databases. Contribute to and improve MLOps workflows for scalable, maintainable model deployment. Clearly present insights and recommendations to both internal teams and client stakeholders. Preferred Requirements: BSc or MSc in a … of machine learning, statistics, and time-series forecasting techniques. Proven ability to communicate complex findings to both technical and non-technical audiences. Familiarity with MLOps principles including deployment, version control, and monitoring would be a great plus. A strong interest will also be considered. Self-driven with the ability to More ❯