ML Platform Engineer at Guidewire Software
Overview
Lead the design and evolution of an ML platform enabling efficient model development and deployment at scale. This role drives the creation of scalable infrastructure for machine learning teams to build and operate models securely and reliably. You will collaborate with cross-functional teams to enhance productivity and ensure compliance.
What You'll Do8
- 1Design and develop components of a scalable ML platform supporting the machine learning lifecycle
- 2Build infrastructure for model training experiment tracking and hyperparameter tuning using MLflow Kubeflow SageMaker
- 3Develop automated ML workflows and CI/CD pipelines for machine learning applications
- 4Collaborate with Data Scientists to create reliable model-ready datasets and improve development experience
- 5Optimize ML workloads across cloud infrastructure compute and storage for improved scalability
- 6Implement monitoring logging and testing practices to enhance platform reliability
- 7Participate in design discussions code reviews and technical planning while upholding engineering best practices
- 8Ensure platform components meet security privacy and compliance requirements
Requirements15
- 1Demonstrate ability to leverage AI for daily engineering tasks
- 2Bachelor's or Master's degree in Computer Science Engineering or related field
- 33+ years of software engineering experience including ML or cloud-native platforms
- 4Strong proficiency in Python Go or Java programming languages
- 5Experience with Docker Kubernetes or similar container orchestration systems
- 6Familiarity with MLOps tools like MLflow Kubeflow SageMaker or Databricks
- 7Knowledge of cloud platforms including AWS Azure or GCP
- 8Basic understanding of machine learning workflows and common algorithms
- 9Excellent communication and problem-solving skills
- 10Experience deploying models in production environments
- 11Familiarity with feature stores workflow orchestration tools or model monitoring solutions
- 12Exposure to streaming technologies such as Kafka or Spark
- 13Proficiency with Infrastructure as Code and CI/CD tools like Terraform and TeamCity
- 14Understanding of ML governance reproducibility and model lifecycle management
- 15Background in insurance financial services or other regulated industries
Salary Insight
$124 - $210k per year
Location
Required Skills
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