Build a next-generation ML data and feature platform to significantly improve productivity of ML practitioners
Collaborate closely with ML practitioners and domain experts to ensure high-quality features and labels
Design and build a near-real-time feature computation engine for generating ML features
Operate and manage feature computation pipelines and serving infrastructure for various ML models
Build and scale systems that accelerate training through performant data loading, transformation, and writing
Develop feature stores that enable feature discovery and sharing

Requirements

Experience in building ML or data infrastructure
Strong empathy and passion for providing a fantastic user experience to ML practitioners
Experience in building and operating 24/7 high-traffic and low-latency online applications
Experience with large-scale data processing frameworks such as Spark, Flink, and Kafka
Experience in working with and optimizing Scala and/or Python codebases
Experience with public clouds, especially AWS
Experience in building and operating ML feature stores (Preferred)
Experience with Functional Programming (Preferred)
Experience working with Notebooks such as Jupyter or Polynote (Preferred)

Benefits

Health Plans
Mental Health support
401(k) Retirement Plan with employer match
Stock Option Program
Disability Programs
Health Savings and Flexible Spending Accounts
Family-forming benefits
Life and Serious Injury Benefits
Paid leave of absence programs
Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off
Full-time salaried employees are immediately entitled to flexible time off

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata infrastructurefeature computation enginedata loadingdata transformationdata writinglarge-scale data processingScalaPythonfunctional programming

Soft Skills

empathyuser experience