SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 244,000 - 320,000 / annual
Attentive is an AI marketing platform that combines SMS, RCS, email, and push notifications with real-time behavioral insights to deliver personalized customer experiences. The company serves 8,000+ customers across 70+ industries, including major brands like Crate and Barrel and Urban Outfitters, and has been recognized by Deloitte's Fast 500, Forbes Cloud 100, and LinkedIn Top Startups.
As a Senior Machine Learning Engineer, you will design, build, and operate production-grade ML systems that power real-time personalization across the platform. You'll own ML projects end-to-end—from data exploration and modeling through deployment, monitoring, and iteration. Your work will directly impact hundreds of millions of customer interactions and tens of billions in revenue for Attentive's customers.
Key responsibilities include:
- Designing and scaling ML systems for real-time targeting, decisioning, and personalization
- Owning projects end-to-end with high autonomy and cross-functional collaboration
- Safeguarding model quality through testing, monitoring, validation, and alerting
- Contributing to technical direction and best practices across the ML team
- Mentoring other engineers through code reviews and knowledge sharing
- Improving system reliability, performance, and engineering efficiency
You'll need 6+ years building production ML systems, proven experience owning systems long enough to see downstream impact, and strong proficiency in Python with ML frameworks (PyTorch, TensorFlow, xgboost). Experience with data tools (pandas, Spark, SQL), automated ML pipelines, and cross-functional collaboration is essential.
The tech stack includes Java/Kotlin/Spring Boot microservices, DynamoDB, Aurora, Airflow, Postgres, Redis, and AWS infrastructure. ML work leverages Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas. The company operates with distributed hubs in NYC, San Francisco, London, and Sydney.
