Machine Learning Data Engineer

🚨 Machine Learning Data Engineer (Mid-Level DE/ML Generalist) – Fully Remote at Kalibri We posted the role a few days ago… and received 350+ applications in less than 24 hours. The good news? Massive interest in what we’re building at Kalibri. I personally went through each and every application. Some people have been scheduled. The reality? Most weren’t quite the right fit, so I’ve temporarily taken the public posting down to focus on quality. Here’s exactly what we’re looking for: We need a hands-on generalist who bridges data engineering and machine learning. You’ll own production data pipelines and feature-engineering workflows that power our core AI/ML products (Census, Prediction, Estimation, and OBM) in the hospitality industry. Must-haves: -Strong Python expertise for data pipeline development (non-negotiable) -Solid SQL + cloud data warehouse experience (Snowflake preferred; Databricks or Redshift also fine) -Real hands-on experience with machine learning algorithms — forecasting, prediction models, time-series, or building production features for ML models (e.g., CatBoost, LightGBM, Prophet, etc.) -Experience with orchestration tools (Prefect, Airflow, or similar) and dbt 3–5 years relevant experience as a Data Engineer or ML Engineer Comfortable in a communicative but mostly heads-down, high-ownership environment. These engineers grind. They do not spend a bunch of time theorizing work. This is a mid-level production-focused role, not a senior ML research position and not pure data engineering. At Kalibri, we value people who are solutions-oriented, aligned & accountable, and keep it real (honest, kind, and transparent). Interview Process Overview (designed to be efficient and respectful of your time): -Recruiter Screen (with me – Richie) – ~20min technical + experience discussion -Technical Deep Dive (with HM) – focused on production ML + data engineering skills -Team Collaboration Round – covers technical + day-to-day collaboration -Values & Alignment – short conversation focused on team fit and working style. We aim to keep the process streamlined while ensuring both sides get a clear picture. If this sounds like a strong match (or you know someone perfect), DM me or email me directly and I’ll send you a private application link. Please include a short note on why you’re a fit , especially any examples of production ML pipelines or forecasting/prediction work you’ve done. Let’s cut through the bullshit and connect with the right people. Looking forward to hearing from you! Please share so the right people see this.