dbt Labs
about 8 hours ago
About Us
About the role:
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—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. 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.
You are a good fit if you have:
- 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.
Youll 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.
Qualifications:
- 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.
This is a high-impact, hands-on role where you’ll play a pivotal part in shaping the AI/ML foundation at dbt Labs. If youre excited about solving complex data challenges and building something from scratch, wed love to hear from you! 🚀
Compensation & Benefits
- Salary:
- We offer competitive compensation packages commensurate with experience, including salary, equity, and where applicable, performance-based pay. Our Talent Acquisition Team can answer questions around dbt Labs total rewards during your interview process. In select locations (including Boston, Chicago, Denver, Los Angeles, Philadelphia, New York City, San Francisco, Washington, DC, and Seattle), an alternate range may apply, as specified below.
- The typical starting salary range for this role is: $172,000 - $207,900 USD
- The typical starting salary range for this role in the select locations listed is: $191,000 - $231,000 USD
- Equity Stake
- Benefits - dbt Labs offers:
- Unlimited vacation (and yes we use it!)
- 401k w/3% guaranteed contribution
- Excellent healthcare
- Paid Parental Leave
- Wellness stipend
- Home office stipend, and more!
*Equity or comparable benefits may be offered depending on the legal limitations
What to expect in the hiring process (all video interviews unless accommodations are needed):
- Interview with a Talent Acquisition Partner
- Technical Interview with Hiring Manager
- Coding Challenge
- Systems Design & Product Partner
- Final interview with leadership team member
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Who we are
At dbt Labs, we have developed strong opinions on how companies should practice analytics.
Specifically, we believe that:
- Code-based transformations offer unmatched flexibility and transparency across various “multi-player” development to power everyone in the organization to collaborate on a common language
- Data analysts should adopt similar practices and tools to software developers
- Critical analytics infrastructure should be controlled by its users as open source software
- Analytic code itself — not just analytics tools — will increasingly be open source
It turns out that a lot of other people believe this too! Today, there are 50,000 teams using dbt every week, 100,000 dbt Community members, and 5,100 companies paying for dbt Cloud. Our customers include JetBlue, Hubspot, Vodafone New Zealand, and Dunelm. dbt is synonymous with the practice of analytics engineering, defining an entire industry. We’re backed by top investors including Andreessen Horowitz, Sequoia Capital, and Altimeter.
dbt Labs is an equal opportunity employer. Were committed to building an inclusive team that welcomes a diversity of perspectives, people, and backgrounds regardless of race, color, national origin, gender, sexual orientation, age, religion, disability, citizenship, veteran status, or any other protected status. We feel strongly that whether or not your experience exactly fits the job description, your passion and skills will stand out and set you apart even if your career has taken some twists and turns. If you are on the fence about whether you meet our requirements, we encourage you to apply anyway! Please reach out to us directly at recruiting@dbtlabs.com if you need assistance or an accommodation.
Want to learn more about our focus on Diversity, Equity and Inclusion at dbt Labs? Check out our DEI page here.
dbt Labs reserves the right to amend or withdraw the posting at any time. For employees outside the United States, dbt Labs offers a competitive benefits package. Equity or comparable benefits may be offered depending on the legal or country limitations.