for textual analysis, with an interest in learning more. Experience working with commonly used data science libraries and frameworks, e.g. Spacy, pandas, numpy, scikit-learn, Keras/TensorFlow, PyTorch, LangChain, Huggingface transformers etc. Familiar with both on-premises and cloud-based platforms (e.g. AWS). Working understanding of ML Ops workflows and ability to perform basic model deployment without ML More ❯
distributed state sharing and caching. Knowledge of various DB engines (SQL, Redis, Kafka). Experience with Generative AI and LLM-based applications. Familiarity with AI agents and orchestration frameworks (LangChain, LangGraph). Experience with embeddings and fine-tuning GenAI models. Understanding of ModelOps/ML Ops/LLM Ops. Familiarity with SRE techniques. This role has been deemed Inside IR35 More ❯
through research. We are looking for experience in the following skills and experience: AI/ML platform technologies and services such as Sagemaker/Vertex/Azure ML, OpenAI, Langchain, AutoML, OCR, STT, feature stores, vector DB, ... Implementation of AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG, deployment models Building and using More ❯
knowledge sharing, and confidence-building to help them succeed in their roles. Knowledge and/or experience of Generative AI technologies and tooling e.g. OpenAI or other LLMs, PromptFlow, Langchain Understanding of the benefits and pitfalls of GenAI implementation Diverse and Inclusive At SAS, it's not about fitting into our culture - it's about adding to it. We believe More ❯
evaluation pipelines to assess and optimize model performance Prototype and productionize agentic workflows that leverage tool usage and chaining Experiment with, tune, and benchmark different LLMs (e.g., OpenAI, HuggingFace, LangChain) Automate model evaluation and integrate insights into the dev lifecycle Support semantic search, data extraction, and document analysis use cases Collaborate with legal engineers and product to build secure and … to architectural decisions, internal tooling, and team best practices Experience & Qualifications: 4+ years of backend or AI-focused engineering experience Hands-on experience working with LLMs and related frameworks (LangChain, LangGraph, etc.) Strong programming skills-Python preferred; experience with APIs and cloud infra is a plus Proven track record designing evaluation frameworks and tuning model performance Solid understanding of data More ❯
research Qualification We are looking for experience in the following skills and experience: AI/ML platform technologies and services such as Sagemaker/Vertex/Azure ML, OpenAI, Langchain, AutoML, OCR, STT, feature stores, vector DB, AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG, deployment models Cloud infrastructure (networking, security, storage, monitoring More ❯
Postgres Familiarity with web standards, accessibility, and development best practice Building microservices in C# or Java Experience building solutions that integrate with LLMs using tools such as Vercel AI, Langchain etc. Using the GOV.UK Design System and using Nunjucks WHAT YOU'LL LOVE ABOUT WORKING HERE: We are delighted to have received the "Glassdoor Best Places to work UK' accolade More ❯
such as Java, TypeScript, React, and MySQL. Hands-on experience with AI-assisted development tools like Windsurf, Cursor, GitHub Copilot, and Enterprise ChatGPT. Practical experience with AI tools like LangChain/LangGraph is highly desirable. Exposure to LLM APIs, codegen platforms, vector databases, and agentic frameworks. A disruptor mindset and interest in creating solutions with real-world impact. A passion More ❯
