About the Role

Data is our lifeblood — and you’ll own the systems that keep it flowing. As Member of Technical Staff (Data Platform), you’ll design the pipelines, services, and APIs that get clean, high-quality data into the hands of researchers and into the guts of our training and evaluation systems.

You’ll experiment with new retrieval and processing methods, build dataset quality benchmarks, and ensure that our data infrastructure scales with the demands of large-scale ML.

Responsibilities

• Build, operate, and optimize large-scale ingestion, transformation, and retrieval pipelines

• Design APIs and services for high-throughput, low-latency data access

• Implement data quality benchmarks, versioning, and reproducibility workflows

• Collaborate with ML engineers to integrate datasets into training and evaluation loops

• Ensure strong engineering discipline — version control, reviews, CI/CD, etc

Qualifications

• Deep experience in data engineering and distributed processing systems

• Experience with large-scale storage, streaming, and retrieval systems

• Strong in Python, SQL, and modern data stacks (Kafka / Spark / Polars / Flink / Airflow / Arrow / Flyte / DuckDB etc)

• Startup-ready mindset — adaptable, fast-moving, high-ownership

What makes us interesting

• Small, elite team of ex-founders, researchers from top AI Labs, top CS grads, and engineers from top companies

• True ownership You will not be blocked by bureaucracy, shipping meaningful work within weeks rather than months

• Serious momentum We're well-funded by top investors, moving fast, and focused on execution

What we do

• Ship consumer products powered by cutting-edge AI research, and

• Build infrastructure that facilitates research and product, and

• Innovate cutting-edge research that will open up new consumer product forms

The Details

• Full-time, onsite role in Menlo Park

• Startup hours apply

• Generous salary, with additional benefits to be discussed during the hiring process