6 of 6 Prompt Engineering Jobs in the North East

Stay ahead of market trends in Generative AI, Responsible AI, and emerging AI use cases across sectors. Advise internal stakeholders on how evolving technologies (e.g. vector databases, RAG pipelines, prompt engineering) can drive value in future proposals. Qualifications Experience & Skills Proven experience in pre-sales or client-facing architecture roles involving AI, data science, or analytics. Strong ability More ❯

Doing Designing and building end-to-end AI and ML systems that deliver real business value Leveraging Large Language Models (LLMs) in production environments, with hands-on involvement in: Prompt engineering and agentic workflows Evaluation frameworks and retrieval-augmented generation (RAG) pipelines LLM inference stack concepts: KV caching, speculative decoding, parallel decoding, and other optimization techniques Collaborating with … stakeholders across engineering, data, and business teams to deliver innovative solutions Working across cloud platforms like Azure or AWS Contributing to system architecture and writing clean, production-grade code Communicating findings and recommendations clearly to both technical and non-technical audiences What You’ll Bring Deep understanding of machine learning fundamentals and practical experience building real-world AI systems More ❯

PyTorch, TensorFlow). Solid understanding of machine learning fundamentals , including supervised/unsupervised learning. Experience with cloud environments – ideally Azure , but AWS or GCP also considered. Familiarity with LLMs , prompt engineering , and vector databases (e.g. Pinecone, FAISS). Practical experience building production-ready AI applications. Ability to work on-site in Newcastle in a collaborative, agile environment. A More ❯

PyTorch, TensorFlow). Solid understanding of machine learning fundamentals , including supervised/unsupervised learning. Experience with cloud environments – ideally Azure , but AWS or GCP also considered. Familiarity with LLMs , prompt engineering , and vector databases (e.g., Pinecone, FAISS). Practical experience building production-ready AI applications. Ability to work on-site in Sunderland in a collaborative, agile environment. A More ❯

team of curious, helpful, and independent scientists and engineers, united by a commitment to deliver cutting-edge, well-engineered Machine Learning systems. You will work closely with product and engineering teams across Turnitin to integrate Machine Learning into a broad suite of learning, teaching and integrity products. We are in a unique position to deliver Machine Learning used by … necessary. Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters. Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs. Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings. Optimize models for … learning in other modalities such as vision and speech would be a strong bonus. A strong understanding of the math and theory behind machine learning and deep learning. Software engineering background with 3-5 years of experience (waived for a PhD in Computer Science or related: we use Python, SQL, Unix-based systems, git, and github for collaboration and More ❯

delivery models. The Trainer will support digital transformation by upskilling individuals to become in-house digital enablers, combining technical expertise with change management, risk mitigation, ethical AI use, and prompt engineering skills. The role includes delivering a blend of face-to-face workshops, online training, hands-on labs, and ongoing consultancy-style support aligned to apprenticeship standards. Role … an extended transformation journey, guiding them through real-world activities such as Copilot deployment, semantic indexing, data governance, and AI workflow automation. Coach staff in critical skills such as prompt engineering, AI risk mitigation, ethical considerations, and change leadership to ensure responsible, scalable adoption. Align learning delivery with organisational needs, helping teams to build AI adoption roadmaps, configure More ❯