• 3-4 years of experience in software engineering, DevOps, or related field with a focus on ML systems
• Experience with ML frameworks
• Experience with cloud platforms, preferably AWS
• Experience with container runtime architectures, preferably Kubernetes
• Proficiency with at least one programming language, preferably Python or Typescript
• Familiarity with CI/CD practices and tools
• Experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation
• Strong understanding of distributed systems and microservices architecture
• Ability to work in a fast-paced, changing startup environment

Desirable

• As a Senior Software Engineer, ML Platform, at Fieldguide, you'll be responsible for building and maintaining the infrastructure that powers our ML solutions in the audit and advisory industry
• You'll create scalable, efficient systems for model deployment, monitoring, and continuous improvement, enabling our ML Engineers to deliver impactful solutions
• This role is crucial in bridging the gap between ML development and production-ready systems in our rapidly scaling Series B-stage company
• Be an essential technical contributor at a Series B-stage company as it scales
• Design and implement infrastructure for ML model management, including training, deployment, and monitoring
• Build and maintain platforms for running ML algorithms at scale
• Develop systems for A/B testing, performance monitoring, and continuous model training
• Create and manage ETL infrastructure to support ML workflows
• Implement best practices for MLOps, including version control for models and datasets
• Collaborate with ML Engineers to optimize model performance and resource utilization
• Ensure the scalability, reliability, and security of ML systems
• Stay current with the latest advancements in MLOps and cloud technologies
• Contribute to the development of internal tools and frameworks to improve ML workflow efficiency