Principal Software Engineer, Machine Learning
About this role
Building, scaling, and operating production-grade machine learning systems that power real-time personalization for hundreds of millions of customers is the core focus of this role. Operating within a distributed global workforce, the engineering group develops AI-powered personalization engines that unify SMS, RCS, email, and push notifications to drive performance and loyalty for over 8,000 brand partners.
Created to raise the technical bar across machine learning infrastructure, the position demands a hands-on technical leader who collaborates closely with product and engineering teams. Candidates who thrive in this environment possess a strong aversion to regressions, embrace high-ownership responsibilities, and enjoy solving complex problems within a fast-paced setting.
What you will do
- Design and scale production-grade machine learning systems that deliver real-time personalization across the platform.
- Partner closely with product and engineering teams to drive cross-functional machine learning projects from conception to implementation.
- Implement robust testing techniques and protective measures to prevent regressions and maintain high system quality.
- Contribute directly to active projects while advocating for long-term architectural and technical improvements.
- Build automated processes for large-scale data analysis, model development, model validation, and model deployment.
What you need
- Bring a decade or more of professional experience building complex software systems and observing the long-term consequences of architectural decisions.
- Demonstrate extensive professional background applying machine learning and data analysis to build scalable, data-driven products.
- Show proficiency in Python alongside practical experience with frameworks and libraries such as PyTorch, TensorFlow, xgboost, pandas, and matplotlib.
- Exhibit a proven track record of creating automated, efficient pipelines for large-scale data analyses and modern ML model implementation.
- Possess leadership experience guiding cross-functional machine learning initiatives across multiple teams.
Benefits
- Health & wellness perks
- Equity
- Competitive base salary ranging from $350,000 to $430,000 annually
Skills and tech stack
Questions candidates ask
What is the salary range for this role?
The US base salary range for this full-time position is $350,000 to $430,000 annually, plus equity and benefits. Salary ranges are determined by role, level, and location.
What tools and technologies make up the machine learning tech stack?
Automation is driven by custom and open-source machine learning models built with Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas. Infrastructure runs primarily in Kubernetes hosted in AWS EKS alongside tools like Istio, Datadog, Terraform, CloudFlare, and Helm.
What kind of team will I be working with?
The Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. You will partner closely with Product and Engineering while operating with a high degree of ownership.
Should I still apply if I do not meet every single requirement?
If you do not meet all the requirements listed here, the company still encourages you to apply. No job description is perfect, and there may be another opportunity that closely matches your skills and experience.