MLOps Jobs in Nottingham

4 of 4 MLOps Jobs in Nottingham

Staff AI/ML Engineer

Nottingham, UK
Hybrid / WFH Options
SR2 | Socially Responsible Recruitment | Certified B CorporationTM
leveraging cloud-native tools and services. AI Feature Integration Collaborate with engineering and product teams to embed AI-driven functionality into user-facing software. Technical Leadership Set standards for MLOps, automation, and performance tuning across the engineering team. Generative AI & LLMs Explore and integrate modern techniques such as large language models and generative architectures. Mentorship & Collaboration Support peers through code More ❯
Employment Type: Full-time
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Machine Learning Engineer Trainer

Nottingham, England, United Kingdom
Hybrid / WFH Options
FIND | Creating Futures
/Instructor/Lecturer/Teacher Consultant/Coach/Mentor/Educator ) Ability to explain complex topics clearly and adapt to different learning levels. Desirables: Familiarity with modern MLOps practices, reproducibility, and collaborative workflows. Practical experience deploying or training models in cloud environments (AWS, GCP or Azure) This is a fully remote working position & salary is £65,000, with More ❯
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AI Specialist - Automation & Integration

Nottingham, UK
FMCG Exec
independently in a hybrid or remote environment. Experience working in agile environments and iterating based on user feedback. Preferred Skills: Background in deploying AI/ML models to production (MLOps). Experience using cloud platforms such as Azure. Interest or experience in building autonomous agents or internal AI assistants. Why Join? Competitive salary, pension and attractive benefits package. Work on More ❯
Employment Type: Full-time
Posted:

Machine Learning Engineer | £50k–£70k + Equity | Remote (UK)

Nottingham, England, United Kingdom
Hybrid / WFH Options
JR United Kingdom
AI features, including retrieval-augmented generation (RAG), internal LLM-based tools, and content delivery workflows. Experience with vector stores, agent frameworks, or scalable data workflows is all relevant here. MLOps & Deployment: Build and maintain the infrastructure behind our AI stack – including serving models via APIs, monitoring performance, and deploying systems to the cloud. AWS is a plus, but experience with More ❯
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