Machine Learning Platform Engineer

Summary

Job Description

• Design and implement core ML infrastructure for model training hyperparameter tuning experiment tracking and model registry using cloudnative and opensource technologies.

• Contribute to evolving a scalable secure ML platform that supports the end-to-end ML lifecycle including data preparation training evaluation deployment and monitoring.

• Orchestrate ML workflows using tools such as Kubeflow SageMaker MLflow Vertex AI or Databricks ensuring reproducibility and robust automation.

• Partner with Data Engineers to build reliable highquality data pipelines and feature pipelines that provide modelready datasets at scale.

• Implement and improve CI/CD for ML including automated testing validation and safe rollout/rollback of models and data pipelines.

• Optimize ML workload performance and cost across compute storage and networking layers on public cloud (AWS GCP or Azure).

• Embed observability and governance into the platform including logging tracing model performance monitoring and drift detection.

• Collaborate with security compliance and data governance teams to ensure the platform adheres to Guidewires standards for security privacy and auditability.

• Provide technical leadership and mentorship to other engineers influencing architectural decisions coding standards and best practices for ML platform and MLOps.

• Continuously explore and apply AI/automation (including GenAI) to improve developer and data scientist productivity platform reliability and operational efficiency.

What youll bring:

• Demonstrated ability to embrace AI and use datadriven insights to drive innovation productivity and continuous improvement in your current role.

• Bachelors or Masters degree in Computer Science Engineering or a related field.

• 6 years of software engineering experience including 3 years working on ML platforms or infrastructure.

• Expertise in building largescale distributed systems and microservices with solid understanding of system design and architecture.

• Strong programming skills in Python Go or Java with emphasis on writing clean testable maintainable code.

• Handson experience with containerization and orchestration for example Docker and Kubernetes.

• Familiarity with MLOps tools such as MLflow Kubeflow SageMaker and how they fit into an endtoend ML platform.

• Cloud platform experience on AWS GCP or Azure including core services for compute storage networking and identity.

• Experience with statistical learning algorithms (e.g. GLM XGBoost Random Forest) and deep learning approaches (e.g. neural networks transformers) with a practical understanding of how they are trained and deployed.

• Strong communication leadership and problemsolving skills with the ability to influence across functions and work effectively in a global distributed environment.

Preferred :

• Experience with realtime model inference and streaming ML pipelines including lowlatency serving and online feature computation.

• Deep knowledge of model governance reproducibility and monitoring including experiment lineage versioning and approval workflows.

• Understanding of model performance metrics and drift detection and experience implementing monitoring for data drift concept drift and model quality.

• Exposure to feature stores (e.g. Feast Tecton) and workflow orchestration tools (e.g. Airflow Argo) in production environments.

• Familiarity with regulatory and compliance considerations for ML systems including model auditability interpretability and data privacy laws such as CCPA/GDPR.

• Experience with realtime data pipelines and streaming technologies such as Kafka Flink or Spark Structured Streaming.

• Experience using TeamCity and Terraform (or similar tools) for infrastructureascode and CI/CD of platform components.

• Domain experience in insurance or related industries (such as banking or finance) or a demonstrated ability to ramp quickly in highly regulated domains.

About Guidewire

Guidewire is the platform P&C insurers trust to engage innovate and grow efficiently. We combine digital core analytics and AI to deliver our platform as a cloud service. More than 540 insurers in 40 countries from new ventures to the largest and most complex in the world run on Guidewire.

As a partner to our customers we continually evolve to enable their success. We are proud of our unparalleled implementation track record with 1600 successful projects supported by the largest R&D team and partner ecosystem in the industry. Our Marketplace provides hundreds of applications that accelerate integration localization and innovation.

For more information please visit and follow us on Twitter: @GuidewirePandC.

Guidewire Software Inc. is proud to be an equal opportunity and affirmative action employer. We are committed to an inclusive workplace and believe that a diversity of perspectives abilities and cultures is a key to our success. Qualified applicants will receive consideration without regard to race color ancestry religion sex national origin citizenship marital status age sexual orientation gender identity gender expression veteran status or disability. All offers are contingent upon passing a criminal history and other background checks where its applicable to the position.