Remote Senior Platform Engineer, Machine Learning

Summary

Join Fieldguide as a Senior Platform Engineer, Machine Learning, and build the infrastructure that powers our ML solutions in the audit and advisory industry. As an early engineer at a company with product-market fit, you'll have the opportunity to make a significant impact on our rapidly scaling Series B-stage company.

Requirements

• 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

Responsibilities

• 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

Preferred Qualifications

• Experience with distributed computing frameworks (e.g., Apache Spark)
• Familiarity with ML experiment tracking tools (e.g., MLFlow, Weights & Biases)
• Knowledge of data versioning and feature store technologies
• Experience with high-volume, real-time data processing
• Familiarity with data security and access control for ML systems
• Experience with cloud cost management and optimization for ML workloads

Benefits

• Competitive compensation packages with meaningful ownership
• Unlimited PTO
• 401k
• Wellness benefits, including a bundle of free therapy sessions
• Technology & Work from Home reimbursement
• Flexible work schedules