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Data Platform Engineer
Weights and Biases San Francisco, CA
$142k-174k (estimate)
Full Time | Business Services 1 Month Ago
Save

Weights and Biases is Hiring a Data Platform Engineer Near San Francisco, CA

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.

You will collaborate with Data Scientists, Machine Learning Engineers, and Product Engineers to instrument and quantify our ML tools. Through this role you will have frequent opportunities to build the core data pipelines that enable recommendations to the organizational leaders. 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.

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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.
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.
Our 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
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We encourage you to apply even if your experience doesn't perfectly align with the job description as we seek out diverse and creative perspectives. Team members who love to learn and collaborate in an inclusive environment will flourish with us. We are an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need additional accommodations to feel comfortable during your interview process, reach out at careers@wandb.com.

#LI-Remote

Job Summary

JOB TYPE

Full Time

INDUSTRY

Business Services

SALARY

$142k-174k (estimate)

POST DATE

03/22/2024

EXPIRATION DATE

05/21/2024

WEBSITE

wandb.com

HEADQUARTERS

SAN FRANCISCO, CA

SIZE

<25

FOUNDED

2017

TYPE

Private

CEO

OTIS LANDERHOLM

REVENUE

<$5M

INDUSTRY

Business Services

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About Weights and Biases

Weights & Biases develops machine learning tools that allow users to track and optimize hyperparameters and system metrics for businesses.

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