Machine Learning Engineer



Software Engineering
Fremont, CA, USA
Posted on Sunday, September 10, 2023

About Weee!

Weee! is the largest and fastest-growing ethnic e-grocer in the United States, operating in one of the largest underserved categories in retail with affordable access to exciting ethnic food. By partnering with local suppliers, redesigning the value chain and leveraging social buying, Weee! is reshaping the grocery business entirely. You can read more about us on Business Insider, Reuters and TechCrunch.

Weee! is headquartered in Fremont, CA, and is currently available coast to coast with exceptional growth (5x YoY) across geographies, categories and ethnicities. We have raised $800M+ in funding to date from leading investors including Softbank Vision Funds, DST, Blackstone, Tiger Global, Lightspeed Ventures, Goodwater Capital, XVC and iFly. The opportunity now is to join a rocketship as we prepare for the next stage of growth, and an eventual public listing.

About the Role:

We are seeking a Machine Learning Engineer to join our innovative team. This position is perfect for individuals with a solid background in Machine Learning or Ranking infrastructure, with a distinct advantage for those having 2 years of experience in ML infrastructure, tooling, or backend. You will play a critical role in building and optimizing our ranking/recommendation services, contributing to their reliability and speed, and ensuring their user-friendliness for other team members.


  • Develop and optimize reliable, fast-running ranking and recommendation services
  • Collaborate with backend teams to enhance the interconnectivity and efficiency of the services.
  • Incorporate the usage of real-time signals into the recommendation service for better output.
  • Implement effective workflows for model lifecycle management, simplifying processes for team members.
  • Contribute to problem-solving efforts as a proactive and continuous learner dedicated to developing the most efficient solutions.

Basic Requirements:

  • A Master’s degree or equivalent experience in a quantitative discipline such as computer science, engineering, math, statistics, or physics.
  • Professional aptitude in Java, coupled with a strong proficiency in Python.
  • Solid understanding of deep learning and recommendation service.
  • Proficient SQL skills.
  • Ability to thrive in a fast-paced, startup environment and deliver excellent results.
  • Strong communication skills with the ability to interface with multiple stakeholders.

Preferred Requirements:

  • Prior working experience in ranking and recommendation services.
  • Proven experience working with product teams and backend engineers.
  • Familiarity with tools such as Spark, Flink, TensorFlow, PyTorch, Langchain.
  • Experience with AWS Sagemaker and Cloudwatch is desirable.
  • Proven ability to navigate and resolve ambiguous problems.

Join our team and make a significant contribution towards creating a next-generation shopping and food sharing experience for Weee! customers. We value those who are driven by a passion for substantial impact and continuous learning.


  • Comprehensive health insurance package, including medical, dental, and vision. PPO/HMO packages
  • 401k, 4% company match
  • Equity
  • Annual bonus plan, bi-annual pay out
  • Vacation and holiday time off
  • Monthly mobile stipend
  • Monthly Weee! Points credits

Compensation Range

  • The US base salary range for this full-time position is $130,000 - $160,000
  • This role may be eligible to discretionary bonus, incentives and benefits
  • Our salary ranges are determined by role, level, and location

The range displayed on each job posting reflects the minimum and maximum base salary for new hires for the position across all US locations. Within the range, individual pay is determined by multiple factors like job-related skills, experience and work locations. Your recruiter can share more about the specific salary range during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include any variable compensation elements.

For more jobs and to find out more about Weee!, visit our career page: