Staff Software Engineer, Machine Learning

Role overview

This is a senior Machine Learning Engineering role focused on building, scaling, and operating production-grade ML systems that power real-time personalization for hundreds of millions of end users across thousands of brands. The position operates with a high degree of ownership in a fast-paced, high-impact environment, partnering closely with Product and Engineering peers to raise the technical bar across the ML stack.

Responsibilities

- Design, build, and maintain production ML systems that deliver real-time personalization at very large scale. - Champion code quality and proactively guard against regressions through rigorous testing, monitoring, and review practices. - Serve as a technical leader and collaborator, communicating clearly across product, engineering, and data functions. - Drive both hands-on contributions and longer-term advocacy for larger improvements to project quality. - Lead cross-functional ML initiatives from research exploration through deployment, validation, and ongoing iteration.

Requirements

- Approximately 10+ years of professional experience, including 6+ years building production systems with enough tenure on a single system to observe long-term consequences of design decisions. - Strong proficiency in Python and hands-on experience with ML frameworks such as TensorFlow or PyTorch, along with tooling like xgboost, pandas, matplotlib, SQL, and Spark or equivalents. - Extensive track record applying machine learning and data analysis to build scalable, data-driven products in collaboration with cross-functional teams. - Demonstrated experience designing scalable, efficient, and automated pipelines for large-scale data analysis, model development, model validation, and model implementation grounded in modern research. - Proven ability to lead cross-functional machine learning projects across teams.

Nice to have

- Background working in a late-stage startup environment where impact and pace are high. - Familiarity with infrastructure run on Kubernetes (for example, hosted via managed services like AWS EKS) and tooling such as Istio, Datadog, Terraform, Cloudflare, and Helm. - Exposure to backend microservices, streaming and workflow systems, GraphQL-based frontends, and ML orchestration tools like Metaflow or Airflow.

Benefits and work setup

- The US-based base salary range for this full-time position is approximately $320,000 to $360,000 annually, plus equity and benefits. - Compensation varies by role, level, and location. - Benefits include competitive health and wellness offerings and equity support intended to help employees bring their best to work.