Lancaster, Lancashire, United Kingdom Hybrid / WFH Options
Galaxy Systems
Experience with ML lifecycle management tools like AWS SageMaker, MLflow, or Databricks. Working knowledge of CUDA, Nvidia GPUs, and distributed training. Experience with AWS services (S3, Lambda, EC2, SageMaker, Bedrock, etc.). Desired: Experience deploying models as APIs/microservices in cloud-native environments. Familiarity with prompt tuning, embedding generation, vector search, and knowledge retrieval frameworks. Understanding of MLOps More ❯
expertise in one or more of the following technology areas: NoSQL, such as DocumentDB/MongoDB RDF Graph database such as GraphDB ML/AI such as Sagemaker/Bedrock Search technologies such as SOLR or Opensearch/ElasticSearch Data pipeline engineering utilising cloud-based technologies (AWS) Write high quality clean, testable code, with a focus on incremental innovation. More ❯
reasoning, memory modules, and RAG pipelines. Use frameworks like LangChain, LangGraph, CrewAI, and tools like Pinecone, FAISS. Optimize performance and ensure responsible AI practices. Deploy via cloud platforms (AWS Bedrock, Azure AI, Google Vertex). Build UIs (Streamlit, Gradio, React) and integrate APIs and databases. Preferred Skills Experience with multi-agent systems and ethical AI. Familiarity with advanced model More ❯
to hand yourself in front of a customer who have problems and work out viable solutions- AI or ML experience highly beneficial- Experience with any of the following: AWS Bedrock, Agent2Agent Protocol (A2A), or other agentic AI solutions beneficial If this sounds of interest, please apply for this role. More ❯
