7 of 7 MLOps Jobs in the North West

Deep technical proficiency with LLMs, NLP, Python, SQL, and major AI/ML frameworks (e.g., PyTorch, TensorFlow). Strong understanding of AI engineering fundamentals including DevOps, CI/CD, MLOps, and DevSecOps. Experience building AI governance frameworks to address ethical risk, model accuracy, and regulatory compliance. Why Join? This is a career-defining opportunity to shape the AI strategy of More ❯

initiatives. Experience required: AWS Data/ML Engineering & ML Ops (ECS, Sagemaker) CI/CD pipelines (GitLab, Jenkins) Python, PySpark & Big Data ecosystems AI/ML lifecycle, deployment & monitoring MLOps tooling (MLflow, Airflow, Docker, Kubernetes) Front-end exposure (HTML, Flask, Streamlit) RESTful APIs & backend integration If this ML Engineer role is of interest, please apply now for immediate consideration. More ❯

of working with cloud services, and the main challenges involved Understanding and experience of experimentation within data science, e.g. A/B testing Experience with model lifecycle management and MLOps Experience mentoring other team members Additional Information If you can bring some of these skills and experience, along with transferable strengths, we'd love to hear from you and encourage More ❯

will use your skills to: Tune machine learning methods to best leverage our state-of-the-art processing capabilities Deploy and maintain machine learning methods in a DevOps/MLOps based machine learning environment Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards Your work will enable sustained improvements to products … Head of Data Science, and Head of Technical Underwriting Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software. Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible. Tune machine learning methods for … of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc. Experience with deploying services in Docker and Kubernetes Experience in creating production grade coding and SOLID programming principles More ❯

Tesco, Sainsbury's, O2, Halifax, AA, Saga and Lloyds Bank to list a few. As a Machine Learning Engineer, you will help build and maintain the pricing team's MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function. Key … Responsibilities: Build an MLOps/DevOps environment to support machine learning automation Build the pipelines that automate the regular model update and monitoring processes Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation … and communication processes. Work closely with the data science team to integrate modelling approaches and techniques Key Skills and Experience: Previous experience as a DevOps/MLOps engineer Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud) Understanding of machine learning models and the modelling process, from data ingestion and More ❯

JOB VACANCY GLOBAL LOGIC Company: Global Logic Job Title: GTM Solutions Architect, AI/ML - Intelligent Enterprise Location: United Kingdom - Edinburgh, London, Manchester Working style: Hybrid You'll be part of a collaborative, entrepreneurial environment that values innovation, excellence, and More ❯

to join our team in Radbroke. This hybrid role offers the opportunity to work on cutting-edge machine learning and data engineering projects, leveraging the latest cloud technologies and MLOps practices. Required/Primary Skills: AWS Data Engineering ML Engineering ML-Ops ECS, Sagemaker Gitlab Jenkins CI/CD AI Lifecycle Experience in front-end development (HTML, Stream-lit, Flask … with model deployment and monitoring in cloud environments (AWS). Understanding of machine learning lifecycle and data pipelines. Proficiency with Python, Pyspark, Big-data ecosystems Hands-on experience with MLOps tools (e.g., MLflow, Airflow, Docker, Kubernetes) Secondary Skills Experience with RESTful APIs and integrating backend services All profiles will be reviewed against the required skills and experience. Due to the More ❯