reflow - ML Engineer - Remote (Europe)
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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 • 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
• Develop machine learning models to improve user experience on Reflow's platform. • Collaborate with cross-functional teams including product managers and UX designers to understand business needs and translate them into technical requirements for ML solutions. • Conduct data analysis, cleaning, preprocessing, feature engineering, model selection, training, evaluation, tuning, deployment, monitoring, maintenance of machine learning models in production environments. • Stay updated with the latest developments in artificial intelligence research to continuously improve Reflow's products and services using cutting-edge techniques. • Communicate technical concepts effectively within a team setting or when presenting ML solutions to non-technical stakeholders, ensuring alignment of expectations between engineering teams and business units.
Benefits
• Build the learning backbone of Reflow that turns work data into predictions and signals • Work closely with founders, engineers, and product teams • Ship real models into production and see them shape how teams work • Flexible structure, part-time or full-time, with a focus on ownership and iteration speed • 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.
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