ML Platform Engineer - Scalable MLOps & Infrastructure

Gusto; New York (NY); Hybrid; USD 190,000 - 240,000; Full time

Benefits offered by this job

Equity (RSUs)

Competitive benefits

Job summary

Gusto is seeking a Machine Learning Platform Engineer to join our ML Platform team and build out and scale our ML/AI infrastructure. You will work closely with AI/ML engineers to rapidly build, deploy, and iterate high-quality ML/AI infrastructure solutions at scale, ensuring reliability and effectiveness.

The ideal candidate has 5+ years of software engineering experience and strong knowledge of ML data pipelines and infrastructure.

Qualifications

• 5+ years of software engineering experience with Python, Ruby or Java.
• Experience designing infrastructure for ML lifecycle (feature stores, model development, deployment, observability).
• Experience with at least one cloud platform (AWS preferred).
• Curiosity with emerging AI frameworks; apply best practices to scale AI safely.
• Comfort with AI-assisted development tools and staying current with AI approaches.

Responsibilities

• Build core components of our ML/AI Platform roadmap and design MLOps pipelines.
• Develop, maintain, and enhance frameworks for ML model development and deployment.
• Collaborate with ML/AI builders to determine requirements and SLAs for API-enabled services.
• Develop, maintain, and enhance infrastructure supporting ML services.
• Support deployment patterns for ML models with CI/CD pipelines and automated testing.
• Apply AI tools in engineering workflows and promote an AI-native lens to decisions.
• Adopt the latest best practices for using AI technologies across development.

Skills

Python

Ruby

Java

ML infrastructure design

AWS

AI frameworks

AI tooling

Tools

Feature stores

Model development tools

Deployment tools

Observability tools

Job description

Gusto is seeking a Machine Learning Platform Engineer to join our ML Platform team and build out and scale our ML/AI infrastructure. You will work closely with AI/ML engineers to rapidly build, deploy, and iterate high-quality ML/AI infrastructure solutions at scale, ensuring reliability and effectiveness.

The ideal candidate has 5+ years of software engineering experience and strong knowledge of ML data pipelines and infrastructure.