Reflow

Reflow

ML Engineer

Canada · Part-time

Sponsorship not specifiedDetected 176 days ago
PythonMachine LearningTensorFlowPyTorchLLMsForecasting

About the role

  • At the core of Reflow is a growing set of machine learning models that learn from real work patterns to predict outcomes, surface insights, and power intelligent automation.
  • The salary ranges in our job postings are intentionally wide because they need to cover both U.S. and international candidates.

Responsibilities

  • Build predictive models for task outcomes, productivity trends, capacity forecasting, and workflow optimization
  • Design and maintain feature pipelines, training loops, and evaluation frameworks

Requirements

  • Experience training supervised and self-supervised models
  • Hands-on experience with model fine-tuning, evaluation, and deployment workflows
  • Experience fine-tuning large language models or embedding models
  • Familiarity with PyTorch, TensorFlow, or similar frameworks

Skills

  • Our final offer will depend on things like your experience, skill set, and location.

Compensation

  • We offer competitive pay based on the market and where you're located.
  • The salary ranges in our job postings are intentionally wide because they need to cover both U.S. and international candidates.
  • Our final offer will depend on things like your experience, skill set, and location.

Benefits

  • Train, fine-tune, and evaluate machine learning models on real-world workflow and behavioral data
  • Strong foundation in Python and applied machine learning
  • Experience with time series forecasting, behavioral modeling, or graph-based learning
  • Build the learning backbone of Reflow that turns work data into predictions and signals
  • Flexible structure, part-time or full-time, with a focus on ownership and iteration speed

Company info

  • We are building Reflow, a workforce and workflow intelligence platform that helps teams understand and improve how work gets done.

This listing is sourced directly from Reflow's careers page and normalized into a canonical job model.