Data Engineer

Posted 4 Days Ago
2 Locations
Hybrid
180K-250K Annually
Entry level
Software
The Role
The Data Engineer will build and scale Baseten's internal data platform, designing data models and pipelines while enabling self-service analytics and ensuring data reliability.
Summary Generated by Built In

ABOUT BASETEN

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products.

THE ROLE

We’re hiring a Data Engineer to build and scale Baseten’s internal data platform. This role sits at the intersection of data engineering, analytics, and data science, transforming raw product and business data into reliable datasets that power decision-making.

You’ll design the data models, pipelines, and analytics infrastructure that enable teams across Product, Engineering, Finance, Marketing, and Sales to understand usage and performance. This includes working with AI inference, infrastructure, and observability data to generate insights about the product, business operations and platform economics.

You’ll partner closely with stakeholders to build robust, scalable pipelines, define company-wide metrics that inform strategy and planning.

RESPONSIBILITIES

  • Design and maintain core data models and semantic layers

  • Develop and orchestrate batch and streaming data pipelines using technologies such as Apache Beam, Kafka, Airflow, or similar frameworks

  • Analyze inference and infrastructure telemetry, including data from OpenTelemetry, Grafana, and other observability tools

  • Define and maintain company-wide metrics across product usage, performance, and customer lifecycle

  • Enable self-service analytics through agents and tools, with well-structured semantic layers and context

  • Ensure data reliability and quality through testing, documentation, and governance

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PREFERRED QUALIFICATIONS

  • Understanding of inference metrics such as latency, throughput, token usage, and model performance

  • Experience supporting B2B SaaS and/or consumption-based platforms

  • Application of forecasting and predictive modeling (e.g., ARIMA, Prophet) to business processes

BENEFITS

  • Competitive compensation, including meaningful equity.

  • 100% coverage of medical, dental, and vision insurance for employee and dependents

  • Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)

  • Paid parental leave

  • Company-facilitated 401(k)

  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Top Skills

Airflow
Apache Beam
Grafana
Kafka
Opentelemetry
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The Company
59 Employees

What We Do

At Baseten we provide all the infrastructure you need to deploy and serve ML models performantly, scalably, and cost-efficiently. Get started in minutes, and avoid getting tangled in complex deployment processes. You can deploy best-in-class open-source models and take advantage of optimized serving for your own models. We also utilize horizontally scalable services that take you from prototype to production, with light-speed inference on infra that autoscales with your traffic. Best in class doesn't mean breaking the bank. Run your models on the best infrastructure without running up costs by taking advantage of our scaled-to-zero feature

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