Senior Machine Learning Engineer - Platform

Gusto is seeking a Senior Machine Learning Engineer to develop and enhance ML infrastructure solutions. The role involves collaborating with applied science practitioners, building MLOps solutions, and managing the ML model development lifecycle. Candidates should have at least 10 years of software engineering experience and expertise in ML and data infrastructure. Gusto has physical offices but allows remote work with a reliable internet connection.
As a Senior Machine Learning Engineer, you will work closely with applied science practitioners and engineers to rapidly build, deploy, and iterate high-quality ML infrastructure solutions at scale, ensuring both reliability and effectiveness. Your deep expertise in the machine learning model development cycle, along with a strong understanding of data pipelines and data infrastructure will be crucial in developing a dependable and scalable ML infrastructure for all of Gusto to rely on. The ideal candidate is passionate about developing software, developing and documenting optimal processes, working with data, and understanding the needs of end users. A strong grasp of ML and data infrastructure is essential, as you will work with stakeholders to build efficient solutions to help our partners scale x times better. Day-to-day responsibilities include driving core components of the ML Platform technical roadmap to design and build MLOps solutions with automated pipelines and standardized processes to build, deploy, run, monitor, debug, and retrain ML Models; developing, maintaining, and enhancing frameworks for machine learning model development and deployment; collaborating with ML model builders and application owners to determine business requirements and SLAs for API-enabled services; developing, maintaining, and enhancing infrastructure supporting machine learning services; and supporting the development of new patterns for the deployment of machine learning models with CI/CD pipelines and automated testing. Requirements include at least 10 years of software engineering experience (Python, Ruby or Java), demonstrated experience architecting and developing infrastructure and platform services for machine learning lifecycle such as feature stores, model development, deployment, and observability tools and solutions, experience with at least one major cloud platform (AWS preferred but not required), and experience with MLOps tooling such as KubeFlow, AWS Sagemaker, MlFlow, or similar. Gusto has physical office spaces in Denver, San Francisco, and New York City, with expectations for employees based in those locations to work from the office approximately 2-3 days per week. When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. Gusto is an equal opportunity employer committed to diversity and inclusion.