6 of 6 MLOps Jobs in the Midlands

ready ML models. Prepare, transform, and validate complex datasets to ensure high-quality inputs for your models. Utilize cloud platforms (AWS, Azure, GCP) and MLOps practices for seamless deployment and monitoring of ML solutions. Write modular, production-grade code using Python and maintain version control with Git. What ...

your skills in a fast-moving AI environment. Nice to Have (But Not Essential) Experience with vector databases , embeddings, or prompt optimisation. Exposure to MLOps , model deployment, or monitoring tools. Background in data engineering, front-end development, or UX-aware AI applications . Interest or experience in healthcare or regulated ...

essential): Experience working with large language models via APIs or open-source frameworks. Fine-tuning or evaluating generative AI systems. Knowledge of MLOps, monitoring and lifecycle management. Experience with cloud AI/ML services and scalable data platforms. Exposure to reinforcement learning, graph machine learning or advanced deep learning techniques. ...

software engineers to integrate models into production systems Evaluate, test, and improve model performance over time Contribute to data pipelines, model training workflows, and MLOps practices Stay up to date with the latest developments in AI, ML, and data science Document models, experiments, and technical decisions clearly Requirements Master … Have Experience with cloud platforms (AWS, Azure, or GCP) Familiarity with data engineering tools or SQL Exposure to deploying models into production or MLOps concepts Internship, research, or project experience in applied AI Working Arrangements Hybrid role : a mix of office-based work in Northampton and remote working Collaborative, supportive ...

model reliability. Apply best practices in model evaluation, mitigating data leakage, and managing the bias/variance trade-off. Deploy and monitor models using MLOps approaches (Docker, CI/CD, cloud platforms like AWS/Azure/GCP). Collaborate closely with engineering and product teams to integrate ML solutions … model development, training, validation, and optimization. Proven experience deploying and maintaining production ML models. Hands-on experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. Demonstrated ability to work with complex real-world datasets and perform feature engineering. Familiarity with modern ML frameworks and libraries, including PyTorch, TensorFlow, HuggingFace ...

model reliability. Apply best practices in model evaluation, mitigating data leakage, and managing the bias/variance trade-off. Deploy and monitor models using MLOps approaches (Docker, CI/CD, cloud platforms like AWS/Azure/GCP). Collaborate closely with engineering and product teams to integrate ML solutions … model development, training, validation, and optimization. Proven experience deploying and maintaining production ML models. Hands-on experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. Demonstrated ability to work with complex real-world datasets and perform feature engineering. Familiarity with modern ML frameworks and libraries, including PyTorch, TensorFlow, HuggingFace ...

control, testing and technical documentation Work with cross-functional teams to integrate AI solutions into existing platforms and workflows Stay current with advancements in MLOps, DevOps and AI operations, driving continuous improvement Essential Skills for the AI Ops Engineer: Strong experience operating machine learning or AI systems in production environments … compliant and well-governed systems Desirable Skills for the AI Ops Engineer: Experience integrating Python-based services with modern front-end frameworks Familiarity with MLOps practices for deploying, monitoring and managing AI systems Exposure to large-scale enterprise data environments or knowledge management systems Understanding of Agile delivery practices ...