ML Infrastructure Scientist — Remote + Equity

Ascenra; Palo Alto, Northern (CA, KY); Hybrid; USD 114,000 - 235,000; Full time

Benefits offered by this job

Equity

Job summary

Pinterest is seeking a Data & Applied Scientist to advance ML measurement, feature understanding, and causal inference at scale. You will own end-to-end production ML systems and partner cross-functionally to turn research into durable platform capabilities that raise the ceiling for the ML organization.

In this role you’ll translate research-grade workflows into production pipelines using Airflow, WandB & Ray, apply causal inference methods, and design scalable tooling that improves model

Qualifications

• Hands-on ML production experience and ability to translate research workflows into production pipelines.
• Strong Python proficiency and familiarity with ML fundamentals.
• Experience with distributed compute and ML tooling.

Responsibilities

• Translate research-grade DS workflows into production ML pipelines using Airflow, WandB & Ray.
• Apply and productionize causal inference methods to address measurement questions.
• Collaborate with ML engineers and product teams to improve tooling and metrics.
• Develop centralized ML platform tooling for feature and model creation, evaluation and trust.
• Build scalable, trustworthy production ML systems operating daily at scale.

Skills

Python

ML fundamentals

Distributed compute

Education

Bachelor's or Master’s degree in CS or related field

Tools

PyTorch

Airflow

Ray

Spark

WandB

Job description

Pinterest is seeking a Data & Applied Scientist to advance ML measurement, feature understanding, and causal inference at scale. You will own end-to-end production ML systems and partner cross-functionally to turn research into durable platform capabilities that raise the ceiling for the ML organization.

In this role you’ll translate research-grade workflows into production pipelines using Airflow, WandB & Ray, apply causal inference methods, and design scalable tooling that improves model