Senior Machine Learning Engineer
Lancaster, Lancashire, United Kingdom
Hybrid / WFH Options
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 ❯
Employment Type: Permanent
Salary: GBP Annual
Posted: