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Salary: USD 350,000 - 430,000 / annual
Attentive is an AI marketing platform that combines SMS, RCS, email, and push notifications with an AI-powered personalization engine to deliver real-time, bespoke customer experiences. The company serves over 8,000 customers across 70+ industries, including major brands like Crate and Barrel, Urban Outfitters, and Carter's, powering billions of customer interactions and tens of billions in revenue.
As a Principal Software Engineer in Machine Learning, you will play a critical role in building, scaling, and operating production-grade ML systems that drive real-time personalization across the Attentive platform. You will operate with high ownership, partner closely with Product and Engineering teams, and help raise the technical bar across ML systems in a fast-paced, high-impact environment.
Key responsibilities include:
- Building and maintaining systems that meet high quality standards with a focus on preventing regressions through comprehensive testing
- Collaborating across teams as a technical leader and strong communicator
- Continuously improving project quality through direct contributions and long-term advocacy for larger-scale improvements
- Leading cross-functional machine learning projects across teams
- Building scalable, efficient, automated processes for large-scale data analyses, model development, validation, and implementation
- Working with modern ML research and translating it into production systems
The technical environment includes Kubernetes/AWS EKS infrastructure, Java/Spring Boot microservices, React/TypeScript frontend, and ML tooling built with Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas. Additional infrastructure includes Istio, Datadog, Terraform, DynamoDB, Kinesis, Airflow, Postgres, and Redis.
Attentive has a distributed global workforce with hubs in New York City, San Francisco, London, and Sydney. The company has been recognized by Deloitte's Fast 500 (four years running), LinkedIn's Top Startups, Forbes' Cloud 100 (five years running), Inc.'s Best Workplaces, and the Human Rights Campaign Foundation's Corporate Equality Index.
REQUIREMENTS:
- 10+ years of professional experience building systems
- Experience on a single system long enough to understand the consequences of architectural decisions
- Proficiency in Python
- Experience with TensorFlow, PyTorch, XGBoost, Pandas, Matplotlib, SQL, Spark, or similar tools
- Extensive experience using machine learning and data analysis to build scalable systems and data-driven products
- Experience working with cross-functional teams
- Proven track record of building scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation
- Experience leading cross-functional machine learning projects across teams
