Software Engineer & Forecasting & Scheduling

Assembled; Canada; On-site; CAD 80,000 - 110,000; Full time

Job summary

A leading tech company in Canada is seeking a back-end engineer with expertise in statically typed languages like Go, Java, or Rust. The role focuses on developing forecasting interfaces, scheduling thousands of support agents, and enhancing machine learning operations. The ideal candidate should have experience with Python libraries like pandas and a passion for improving performance in statistical and runtime contexts. We encourage diverse applicants who are excited about making an impact to apply.

Qualifications

• Extensive back-end engineering experience in statically typed languages.
• Familiarity with machine learning packages and software.
• Previous experience in ML or algorithmic teams.

Responsibilities

• Develop forecasting interfaces and data pipelines.
• Implement interfaces for scheduling thousands of support agents.
• Enhance MLOps for rapid model deployment.

Skills

Back-end engineering in Go, Java, or Rust

Experience with Python libraries (pandas, SciPy, seaborn)

Machine learning or algorithmic team experience

Commitment to performance

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)

• 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.

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!

For United States Applicants:
Assembled participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the United States.
For United Kingdom Applicants:
Assembled is required to verify your right to work in the UK and will conduct a Right to Work check prior to employment in accordance with applicable law.