Guidewire is looking to solve the problem of delivering operational excellence and transformative innovation for the world’s leading P&C insurance software by architecting and scaling a Machine Learning (ML) platform that powers next-generation products.
Requirements
- Expertise in building large-scale distributed systems and microservices.
- Strong programming skills in Python, Go, or Java.
- Experience with containerization and orchestration (e.g., Docker, Kubernetes).
- Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Databricks.
- Cloud platform experience (AWS, GCP, or Azure).
- Experience with statistical learning algorithms (GLM, XGBoost, Random Forest) and deep learning (neural networks, transformers).
- Experience with real-time model inference and streaming ML pipelines.
Responsibilities
- Architect and guide the design of a scalable, secure ML platform supporting the full ML lifecycle, from data ingestion to model monitoring.
- Design and implement infrastructure for model training, hyperparameter tuning, experiment tracking, and model registry.
- Orchestrate ML workflows using tools such as Kubeflow, SageMaker, MLflow, or similar.
- Collaborate with Data Scientists, MLOps engineers, Data Engineers, and Product Engineering to define best practices for reproducibility, governance, and CI/CD for ML.
- Partner with Data Engineers to build robust data pipelines for model-ready datasets.
- Optimize ML workload performance across compute and storage layers using cloud-native and open-source solutions.
- Lead technical discussions, mentor junior engineers, and help set the technical vision for the ML platform roadmap.
Other
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 10+ years of software engineering experience, including 5+ years working on ML platforms or infrastructure.
- Strong communication, leadership, and problem-solving skills.
- Flexible work environment
- Health and wellness benefits
