Senior AI/ML Platform Engineer, dbt Labs

• Extensive hands-on experience in ML infrastructure, including building pipelines and frameworks from scratch
• Expertise in anomaly detection, fraud detection, predictive analytics, and confidence scoring
• Strong Python skills, with proficiency in PyTorch, TensorFlow, and Spark (PySpark preferred, not Java-based Spark)
• Experience working with data warehouses (Snowflake), streaming systems (Kafka), and large-scale ML systems
• A track record of delivering production-ready ML systems—not just research or Jupyter notebooks
• Ability to thrive in a fast-paced, fully remote, distributed team environment
• 5+ years of experience in ML infrastructure, AI/ML engineering, or data engineering
• Bachelor’s degree in a related field, or equivalent professional experience. OR
• Completed enrollment in related bootcamp
• Experience with high-scale ML infrastructure in a fully remote, asynchronous environment

Desirable

• Our team is tackling one of the biggest challenges in data warehouse cost visibility and optimization—helping executive stakeholders understand and reduce their spend within their dbt projects
• Unlike external vendors, we’re bringing cost visibility directly into dbt, enabling users to detect anomalies, predict spend, and automate remediation
• Design and build the AI/ML infrastructure to power cost anomaly detection and predictive analytics
• Lay the foundation for ML-driven cost optimizations—detecting issues and automating remediation within dbt
• Work hands-on with Snowflake, Kafka, PyTorch, TensorFlow, Ibis, and Pandas to process billions of data points
• Collaborate cross-functionally with Product, Engineering, and Design to integrate ML models into dbt workflows
• Provide technical leadership in defining the AI/ML strategy for cost optimization and efficiency
• Influence the growth of our AI/ML engineering team as we scale

• Interview with a Talent Acquisition Partner
• Technical Interview with Hiring Manager
• Coding Challenge
• Systems Design & Product Partner
• Final interview with leadership team member