Data Engineer

Reposted 2 Months Ago
2 Locations
Hybrid
180K-250K Annually
Entry level
Software
Inference will be the largest market ever created.
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 $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn 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

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

  • (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents

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

  • Paid parental leave

  • Fertility and family-building stipend through Carrot

  • (U.S. only) 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).

Skills Required

  • Experience with data modeling and pipeline development
  • Familiarity with batch and streaming data technologies
  • Knowledge of inference metrics and observability tools

Baseten Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Baseten and has not been reviewed or approved by Baseten.

  • Fair & Transparent Compensation — Feedback suggests pay targets the top of market with explicit ranges in postings and a stated aim to provide 90th percentile salaries with equity. Role descriptions emphasize competitive, experience-based pay bands and meaningful stock grants.
  • Healthcare Strength — Healthcare is described as fully covered for medical, dental, and vision for employees and their families, reducing out-of-pocket costs. This comprehensive coverage is consistently highlighted alongside other core benefits.
  • Leave & Time Off Breadth — Time off policies include unlimited PTO with a minimum expectation of at least four weeks, 16 paid company holidays, and a company-wide winter break. These elements indicate substantial protected time away from work.

Baseten Insights

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The Company
HQ: San Francisco, CA
350 Employees
Year Founded: 2019

What We Do

AI’s future won’t be a few massive models built by a handful of labs. It’ll be millions of specialized models embedded into every product, workflow, and experience by the people closest to the customer. The foundation of that future is inference. Inference determines the performance, reliability, latency, and economics of every AI product. For AI to scale globally, it must be as reliable, fast, cost-effective, and high-quality as possible. That’s why Baseten exists. Companies like Abridge, Cursor, Lovable, Notion, and OpenEvidence depend on Baseten to power mission-critical AI workloads in production.

Why Work With Us

We’re an interdisciplinary team of researchers, engineers, and operators building the Inference Cloud our AI future demands. We’re running at a hard systems problem that requires first-principles thinking across the entire stack. The bar is high. We work hard, move fast, and care deeply about quality.

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