Senior AI/ML Platform Engineer

February 24

Apply Now

Receive Emails with Similar Jobs

dbt Labs

WebsiteLinkedInAll Job Openings

dbt Labs is on a mission to empower data practitioners to create and disseminate organizational knowledge. Since pioneering the practice of analytics engineering through the creation of dbt—the open source data transformation tool made for anyone that knows SQL—we've been fortunate to watch more than 5,000 companies use dbt to build faster and more reliable analytics workflows.

analytics • data engineering • data science

51 - 200 employees

📋 Description

• Are you excited about the challenge of building AI/ML infrastructure from the ground up in a greenfield environment? • Our team is tackling one of the biggest challenges in data warehouse cost visibility and optimization. • This is an opportunity to own the AI/ML foundation for a highly anticipated product that will transform how organizations manage their data costs. • In this role, you can expect to 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.

🎯 Requirements

• 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. • You’ll have an edge if you have: • Experience in ML model evaluation, benchmarking, and automated remediation systems. • A background in building scalable ML platforms that process billions of data points. • Familiarity with cost optimization techniques (CostOps/FinOps) within data platforms and cloud environments. • Prior experience in ML infrastructure engineering at a high-growth startup or large-scale platform.

🏖️ Benefits

• Unlimited vacation (and yes we use it!) • 401k w/3% guaranteed contribution • Excellent healthcare • Paid Parental Leave • Wellness stipend • Home office stipend, and more!