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Salary: USD 320,000 - 360,000 / annual
Attentive is an AI marketing platform that combines SMS, RCS, email, and push notifications with AI-powered personalization 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 interactions and tens of billions in customer revenue.
As a Staff 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
- Proactively protecting against regressions through comprehensive testing techniques
- Collaborating across teams as a technical leader and communicator
- Continuously improving project quality through direct contributions and long-term advocacy for larger-scale changes
- Leading cross-functional machine learning projects
The technical stack includes:
- Infrastructure: Kubernetes (AWS EKS), Istio, Datadog, Terraform, CloudFlare, Helm
- Backend: Java/Spring Boot microservices with DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, Redis on AWS
- Frontend: React, TypeScript, GraphQL, Storybook, Radix UI, Vite, esbuild, Playwright
- ML/Data: Python, Metaflow, HuggingFace, PyTorch, TensorFlow, Pandas, xgboost, Spark, SQL
Attentive is a late-stage, well-funded startup recognized as the #1 SMS marketing provider by G2, included in Deloitte's Fast 500 (four years running), Forbes' Cloud 100 (five years running), LinkedIn's Top Startups, and Inc.'s Best Workplaces. The company operates with distributed global hubs in New York City, San Francisco, London, and Sydney.
REQUIREMENTS:
- 10+ years of professional experience (ideal)
- 6+ years building systems with experience on a single system long enough to see consequences of 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
- Proven track record building scalable, efficient, automated processes for large-scale data analyses, model development, validation, and implementation
- Experience leading cross-functional machine learning projects across teams
- Track record of building high-quality systems with proactive regression prevention
