ML Engineer

Reflow

About The Position

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

Requirements

  • Strong foundation in Python and applied machine learning
  • Experience training supervised and self-supervised models
  • Hands-on experience with model fine-tuning, evaluation, and deployment workflows
  • Comfortable working end-to-end from raw data through training to production inference
  • Pragmatic, curious, and experimental with a bias toward shipping working models

Nice To Haves

  • Experience fine-tuning large language models or embedding models
  • Familiarity with PyTorch, TensorFlow, or similar frameworks
  • Experience with time series forecasting, behavioral modeling, or graph-based learning
  • Background working with messy, real-world product data

Responsibilities

  • Train, fine-tune, and evaluate machine learning models on real-world workflow and behavioral data
  • Build predictive models for task outcomes, productivity trends, capacity forecasting, and workflow optimization
  • Fine-tune large models and foundation models for domain-specific prediction, classification, and embedding tasks
  • Design and maintain feature pipelines, training loops, and evaluation frameworks
  • Work with engineers and product teams to integrate trained models into production systems
  • Monitor model performance and iterate using offline evaluation and live data feedback

Benefits

  • Flexible structure, part-time or full-time, with a focus on ownership and iteration speed
  • Competitive pay based on the market and where you’re located
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