Description:

Fieldguide is a remote-first company focused on automating and streamlining assurance and audit work within cybersecurity, privacy, and ESG.
As a Senior Platform Engineer, Machine Learning, you will build and maintain the infrastructure for ML solutions in the audit and advisory industry.
Your responsibilities include designing and implementing infrastructure for ML model management, building platforms for running ML algorithms at scale, and developing systems for A/B testing and performance monitoring.
You will create and manage ETL infrastructure to support ML workflows and implement best practices for MLOps.
Collaboration with ML Engineers to optimize model performance and resource utilization is essential.
You will ensure the scalability, reliability, and security of ML systems while staying current with advancements in MLOps and cloud technologies.
This role is crucial for bridging the gap between ML development and production-ready systems in a rapidly scaling Series B-stage company.

Requirements:

You should have 3-4 years of experience in software engineering, DevOps, or a related field with a focus on ML systems.
Experience with ML frameworks and cloud platforms, preferably AWS, is required.
Familiarity with container runtime architectures, preferably Kubernetes, is necessary.
Proficiency in at least one programming language, preferably Python or Typescript, is expected.
You should have familiarity with CI/CD practices and tools, as well as experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
A strong understanding of distributed systems and microservices architecture is essential.
The ability to work in a fast-paced, changing startup environment is required.