4 of 4 Remote/Hybrid Amazon SageMaker Jobs in Manchester

path to production - Integrate ML infrastructure with CI/CD systems and cloud platforms Required Skills & Qualifications: - Strong experience with ML platforms — MLflow, Kubeflow, SageMaker, or Vertex AI - Proficiency in Python and infrastructure tooling (Docker, Kubernetes, Terraform) - Experience building automated model training and deployment pipelines - Familiarity with feature stores ...

frameworks (PyTorch, TensorFlow, or XGBoost) - Experience with end-to-end ML pipelines from data ingestion to model serving - Familiarity with ML platforms (SageMaker, Vertex AI, MLflow, or Kubeflow) - Solid understanding of supervised, unsupervised, and reinforcement learning fundamentals - Experience with feature stores, model versioning, and experiment tracking - Strong software engineering ...

core ML libraries (PyTorch, TensorFlow, scikit-learn) - Experience building and deploying LLM integrations or fine-tuned models - Familiarity with model serving infrastructure (e.g., SageMaker, Vertex AI, BentoML) - Solid understanding of vector databases, embeddings, and retrieval systems - Ability to communicate technical findings clearly to non-technical stakeholders Equal Opportunity Employer ...

governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift … closely with Engineering/Data teams in production-first environments Comfortable operating within regulated industries Desirable AWS experience (S3, Athena/Glue, IAM, Lambda) SageMaker or equivalent ML platform experience Financial services domain knowledge (risk, fraud, affordability, payments) Experience with model explainability and governance documentation Package & Benefits Hybrid working ...