12 of 12 MLOps Jobs in Belfast

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

with the founding and AI leadership team and have real influence over architecture, tooling, and technical direction. What You'll Be Working On Production MLOps pipelines for training, evaluation, and deployment LLM-powered workflows for planning, site intelligence, and decision support Graph-based ML models linking spatial, regulatory, demographic ...

influence stakeholders Clear, pragmatic communicator with a delivery-focused mindset Desirable (Not Essential) Experience with PyTorch, TensorFlow, or similar ML frameworks Exposure to MLOps, model monitoring, or AI performance optimisation Frontend collaboration experience (e.g. React-based systems) Cloud-native or containerised deployment experience Why work for us? Lead the development ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

leadership role Strong AWS, DevOps, and cloud-native experience Proficient in Java and Python Experience with agile delivery and SaaS products Understanding of AI, MLOps, and automation Strong communication and stakeholder skills Comfortable supporting US-based customers Nice to have: Startup experience, Azure exposure, UX awareness What’s on Offer ...

leadership role Strong AWS, DevOps, and cloud-native experience Proficient in Java and Python Experience with agile delivery and SaaS products Understanding of AI, MLOps, and automation Strong communication and stakeholder skills Comfortable supporting US-based customers Nice to have: Startup experience, Azure exposure, UX awareness What's on Offer ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

Python Experience leading teams within SaaS, scale-up or high-growth environments Solid understanding of agile delivery and stakeholder management Exposure to AI, automation, MLOps or agentic AI approaches Comfortable working flexibly to support international customers Benefits: Salary dependent on experience Opportunity to shape engineering strategy within a growing ...

production deployment — while mentoring top engineers and collaborating closely with research and infrastructure leaders. You'll combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This … navigating the intersection of research, engineering, and product delivery. Roles & Responsibilities: Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals. Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment. Collaborate with Research, Product, and Infrastructure teams ...

lifecycle, ensuring engineering solutions meet operational needs. Implementing and maintaining secure, scalable architectures in collaboration with cloud, platform, and security teams. Applying DevOps and MLOps practices to support reliable, auditable, and maintainable deployments. Contributing to technical design reviews, estimates, and solution documentation. Supporting proposals and technical inputs to bids where … production ML workflows. Exposure to Generative AI, LLMs, or agent-based systems, including orchestration and integration into wider platforms. Understanding of DevOps/MLOps practices, CI/CD, monitoring, and model governance. Defence & Secure Environment Experience Experience delivering technical solutions within MOD, Defence suppliers, Defence consultancies, or other secure public ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

research and implementation, taking models from concept to production, setting technical standards and supporting junior engineers. The role involves close collaboration with the AI, MLOps and Data Engineering teams, contributing to the wider technical strategy and ensuring models are reliable, maintainable and scalable. Key Responsibilities Design and develop … Carry out analysis to understand model behaviour, drift and explainability. Build and maintain tools for evaluation, prompt testing and dataset preparation. Work with the MLOps engineer to deploy, monitor and retrain models in production. Support CI/CD processes for AI, including version control, reproducibility and rollback workflows. Provide mentorship ...