Software Engineer - Forecasting & Scheduling
Assembled
Job Overview
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Job Description
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)
- 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.
We know great candidates don’t always meet every requirement listed in a job description. If the role excites you and you believe you can make an impact at Assembled, we encourage you to apply. We value diverse perspectives and are committed to building an inclusive workplace where everyone feels like they belong and has the opportunity to do their best work. We look forward to hearing from you!
Key skills/competency
- Forecasting
- Scheduling
- Machine Learning
- Data Pipelines
- Python
- Pandas
- SciPy
- Seaborn
- MLOps
- Algorithmic Optimization
- Workforce Management
- Predictive Modeling
- Scalability
- Backend Development
How to Get Hired at Assembled
- Research Assembled's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight experience in forecasting, scheduling, MLOps, and algorithmic optimization for Assembled.
- Showcase ML expertise: Emphasize Python proficiency with pandas, SciPy, and seaborn in your projects.
- Prepare for technical challenges: Focus on distributed systems, data pipelines, and complex scheduling algorithms.
- Demonstrate impact: Quantify past achievements in predictive modeling or large-scale workforce management.
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