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Machine Learning Engineer — New Products



Software Engineering
San Francisco, CA, USA
Posted on Friday, September 22, 2023

Assembled is building software to transform and elevate customer support teams, which often represent 20-50% of the people at a company. Our workforce management platform helps some of the fastest-growing, most innovative companies in the world—including Stripe, Zoom, and Robinhood—to schedule, forecast, and organize their support teams. We’ve raised $70m in funding from the likes of NEA, Emergence Capital, and Stripe itself. You’ll be joining a special group of people who learned the ropes at companies like Stripe, Google, Palantir, Atlassian, Twitter, Airbnb, Looker, NEA, Bain, and more.

The Team

Our New Products Team is building a new AI-based product to help support agents become more efficient. The team acts as a “startup within a startup” and consists of 2 dedicated engineers, 1 business generalist, and is led by our CTO John Wang. We’re looking to add a machine learning engineer who’s been an early hire before and thrives in ambiguity.

We encourage you to learn more about our team and what we’re working on here.


The scope of this role is broad, as would be your impact on the product. While this is an engineering position, you’d also be required to lean into your user research and product management skills, working directly with customers and influencing our roadmap. Below are highlights of what this person will work on:

  • Prototype AI model quality improvements: Constantly improve the performance of our large language models via prompt engineering, fine tuning, and other techniques. You’ll be expected to stay up to date with the latest best practices in AI.
  • Drive the development of our evaluation framework. Serve as the primary force behind the next iteration of our evaluation framework. You’ll ensure that we’re able to quickly and accurately evaluate the performance of our AI models.
  • Improve precision/recall of our document search: Determine the best ways to improve our document retrieval: whether it’s changing our embeddings, tweaking our search parameters, or something else.
  • Deeply embed with users: Work directly with our users to understand how they’re using our new product and use this knowledge to improve our models.
  • Wear many hats: Whether coding, talking to users, planning, brainstorming, interviewing teammates, or collaborating with various teams, be ready to embrace diverse challenges.
  • Influence the product roadmap: Collaborate with the rest of the team to shape and execute the product strategy. Your insights and expertise will be key in identifying opportunities and setting the direction that aligns with our team’s vision.
  • Shape the culture: Foster a startup mindset within the team, characterized by optimism, product obsession, and a bias toward action.

About You

  • 4 years of professional experience in a data science or machine learning role where you’ve used statistical inference to drive actionable recommendations and/or built predictive models while evaluating their effectiveness.
  • 3 years of experience writing production code, ideally with familiarity with Python or Golang.
  • Experience being one of the first employees at a startup (ideally at 20 or fewer people), and the desire to do it again.
  • Demonstrated expertise working with relational databases.
  • Ability to quickly transform raw data to build your own data sets.
  • Quick to act, adapt, and find solutions, often with less data or certainty.
  • Excited to work directly with customers.

The estimated base salary range for this role is $140,000 - $220,000 per year. The base pay offered may vary depending on location, job-related knowledge, skills, and experience. Stock options are provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered.

Our U.S. benefits

  • Generous medical, dental, and vision benefits
  • Paid company holidays, sick time, and unlimited time off
  • Monthly credits to spend on each: professional development, general wellness, Assembled customers, commuting and community-support agriculture (CSA)
  • Paid parental leave and family planning support
  • Hybrid work model with catered lunches everyday (M-F), snacks, and beverages in our SF & NY offices
  • 401(k) plan enrollment