Data Platform Engineer

March 21

Weights & Biases

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Developer-first MLOps platform.

deep learning • developer tools • machine learning • MLOps

51 - 200

💰 Corporate Round on 2022-05

Description

• At Weights & Biases, our mission is to build the best developer tools for machine learning. Weights & Biases is a series C company with $250 million in funding and a rapidly growing user base. Our platform is an essential piece of the daily work for machine learning engineers, from academic research institutions like FAIR and UC Berkeley to massive enterprise teams including iRobot, OpenAI, Toyota Research Institute, Samsung, NVIDIA, Salesforce, Blue Cross Blue Shield, Lyft, and more. • Responsibilities: Deep experience (practical and theoretical) with Data Engineering and the accompanying workflows. History of writing easy-to-follow code and effective documentation for your projects. Expert knowledge of data orchestration/data pipeline tools (dbt, dagster, airflow, etc). Strong skills of working with a real data warehouse utilized daily. Expert knowledge and understanding of web apps and best practices for logging and event instrumentation. Theoretical or practical knowledge of machine learning workflows and terminology. Ability to clearly communicate your ideas to folks across a range of backgrounds and levels of technical knowledge. • Data Science at W&B is a pillar of the product, business, and culture; as such the Data Science team informs strategy directly, and partners with all parts of the business to build a data-first habit.

Requirements

• Deep experience with Data Engineering and the accompanying dataOps workflows. • Knowledge of Dbt, Airflow, Ansible, Argo, or other data pipeline systems; ideally experience building and maintaining a data warehouse. • Strong skills of working with a real data warehouse utilized daily. • Theoretical or practical understanding of machine learning workflows and terminology. • Working knowledge and understanding of web apps and best practices for logging and event instrumentation. • Excitement for MLOps and the Deep Learning toolchains. • History of writing easy-to-follow code and effective documentation for your projects. • Ability to clearly communicate your ideas to folks across a range of backgrounds and levels of technical knowledge.

Benefits

• Flexible time off • Medical, Dental, and Vision for employees and Family Coverage • Remote first culture with in-office flexibility in San Francisco • Home office budget with a new high-powered laptop • Truly competitive salary and equity • 12 weeks of Parental leave (U.S. specific) • 401(k) (U.S. specific) • Supplemental benefits may be available depending on your location • Explore benefits by country