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Assembled

Software Engineer - Forecasting & Scheduling

Posted Yesterday
Remote
Hiring Remotely in United States
135K-280K Annually
Mid level
Remote
Hiring Remotely in United States
135K-280K Annually
Mid level
Develop forecasting interfaces and data pipelines for support contact volume prediction. Design scheduling systems for thousands of agents, enhance MLOps for rapid deployment.
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About Assembled

Great customer support requires human agents and AI in perfect balance, and Assembled is the only unified platform that orchestrates both at scale. Companies like Canva, Etsy, and Robinhood use Assembled to coordinate their entire support operation — in-house agents, BPOs, and AI — in a single operating system. With AI Agents that resolve cases end-to-end, AI Copilot for agent assistance, and AI-powered workforce management that optimizes both human and AI capacity, Assembled helps teams deliver faster, better service while making smarter decisions about how to staff and automate. Backed by $70M from NEA, Emergence Capital, and Stripe, we're building the platform that makes AI and human collaboration actually work.

What you’ll work on
  • Predicting contact volume: Developing forecasting interfaces, data pipelines, and inference servers to predict support contact volume and determine the optimal number of support agents required for specific days and times.

  • Scheduling 1000s of support agents: Designing and implementing interfaces to collect and store team preferences and customer business constraints (e.g., labor laws), enabling the creation of optimal schedules for teams of thousands of support agents based on these forecasts and constraints. (check out https://en.wikipedia.org/wiki/Nurse_scheduling_problem)

  • MLOps: Enhancing machine learning efficiency and operations to support rapid model deployment and iteration.

About you (specifically)
  • Experience with translatable languages: Extensive back-end engineering experience in statically typed languages like Go, Java, or Rust.

  • Familiarity with ML packages and software: Experience using Python libraries like pandas, SciPy, and seaborn for statistical or predictive work.

  • Background in ML or algorithmic teams: Previous experience working on a machine learning or algorithmic team.

  • Passion for performance: A strong commitment to advancing both statistical and runtime performance, ensuring reliable and efficient forecasting and scheduling.

Top Skills

Go
Java
Pandas
Python
Rust
Scipy
Seaborn

What you need to know about the Colorado Tech Scene

With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.

Key Facts About Colorado Tech

  • Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
  • Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
  • Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
  • Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute

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