Senior Machine Learning Engineer
Lancaster, Lancashire, United Kingdom
Hybrid / WFH Options
Hybrid / WFH Options
Galaxy Systems
GPT, Claude, or other LLMs integrated with document retrieval systems. Develop production-ready ML applications in cloud environments (AWS, SageMaker, Databricks, etc.). Leverage GPU-based computing resources and CUDA/Nvidia for performance optimization in training and inference. Collaborate with data engineers, software developers, and product teams to deliver AI/ML capabilities in production. Conduct rigorous model … transformer-based models. Practical knowledge of LLM integration (e.g., GPT, Claude) and RAG architecture. 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 More ❯
Employment Type: Permanent
Salary: GBP Annual
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