excellence 🧠 What We’re Looking For 5+ years of commercial PHP experience Solid understanding of cloud infrastructure (preferably GCP) Experience with MySQL, NoSQL (Cassandra) Skilled in TDD , debugging, and performanceoptimisation Bonus points for Kubernetes experience Tech stack: PHP, nginx, RabbitMQ, Google Cloud Platform (GCP), custom frameworks (full training provided) 🎁 What’s in It for You Alongside a … fantastic culture, modern office and regular company events, our partner offers: 💰 Up to £60,000 DOE + 10% personal performance bonus 🏖️ 28 days holiday (plus birthday off + length of service accrual) 🍳 Free breakfast, lunch, drinks & snacks every day 💪 Gym, golf membership & onsite gym 💅 Onsite hairdresser, barista & cocktail bar 🎬 Netflix & Spotify subscriptions 🦷 BUPA Health & Dental care 🧘 ♂️ BUPA Peak Assessments More ❯
support enterprise-grade LLM applications. MLOps and LLMOps : Build and maintain scalable MLOps and LLMOps pipelines, enabling automation of model training, testing, deployment, and monitoring. Enable reproducibility, traceability, and performance optimization across all AI solutions. Vendor Product Evaluation & Onboarding : Lead the technical evaluation of third-party AI products and platforms, conducting benchmarking, sandbox testing, and assessing integration feasibility. Collaborate … while managing feature stores and internal knowledge bases for RAG. Strong grasp of prompt engineering techniques, including zero-shot and few-shot prompting strategies with ability to enhance the performance of LLMs and agentic AI systems. Familiarity of LLM model evaluation techniques such as ROUGE, LLM-as-a-Judge and BERT. Deep knowledge of cloud-native AI platforms and … design and implement scalable ML, LLM pipelines and infrastructure. Skilled in benchmarking, sandbox testing, and integration of vendor AI products. Strong analytical and problem-solving skills, with attention to performance optimization Effective communication and collaboration skills for cross-functional engagement with engineering, procurement, legal, and governance teams. Qualifications PhD/MSc in Computer Science, AI, Data Science, or related More ❯
support enterprise-grade LLM applications. MLOps and LLMOps : Build and maintain scalable MLOps and LLMOps pipelines, enabling automation of model training, testing, deployment, and monitoring. Enable reproducibility, traceability, and performance optimization across all AI solutions. Vendor Product Evaluation & Onboarding : Lead the technical evaluation of third-party AI products and platforms, conducting benchmarking, sandbox testing, and assessing integration feasibility. Collaborate … while managing feature stores and internal knowledge bases for RAG. Strong grasp of prompt engineering techniques, including zero-shot and few-shot prompting strategies with ability to enhance the performance of LLMs and agentic AI systems. Familiarity of LLM model evaluation techniques such as ROUGE, LLM-as-a-Judge and BERT. Deep knowledge of cloud-native AI platforms and … design and implement scalable ML, LLM pipelines and infrastructure. Skilled in benchmarking, sandbox testing, and integration of vendor AI products. Strong analytical and problem-solving skills, with attention to performance optimization Effective communication and collaboration skills for cross-functional engagement with engineering, procurement, legal, and governance teams. Qualifications PhD/MSc in Computer Science, AI, Data Science, or related More ❯
