5 of 5 MLOps Jobs in Liverpool

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 ...

Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps, or secure communications. Knowledge of ethics, bias mitigation, and fairness in AI. Familiarity with justice technology, corrections, or secure IT systems. Contributions to AI research ...

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 ...

Consulting & Mentorship: Act as the internal authority and consultant, providing technical guidance, architectural review, and mentorship to junior data scientists and engineering teams. MLOps & Governance: Establish best practices for MLOps, model monitoring, version control, and model risk governance in a multi-cloud production environment. Required Skills and Expertise (10+ Years ...

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 ...