> Markdown version of [/jobs/ext/4619486-machine-learning-engineer-discovery](https://www.wearedevelopers.com/jobs/ext/4619486-machine-learning-engineer-discovery). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer, Discovery - **Company:** Whatnot Inc. - **Location:** New York, NY, United States (Remote available) - **Experience:** Experienced - **Salary:** $180,000 - $245,000 - **Contract:** Permanent contract - **Skills:** Data Visualization, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Feature Engineering, Pytorch, Backend, Xgboost, Machine Learning Operations - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25197_b6424602bfabe3a26d9e3736ad3bcabe ## About the Role Curious about who thrives at Whatnot? We've found that embodying a low ego, growth mindset, and high-impact drive goes a long way here. As our next Machine Learning Scientist you should have: * 4+ years of industry experience building and deploying ML models to solve user problems at scale * Industry experience with a track record of applying scientific methods to solve real-world problems on consumer scale data. * Advanced proficiency in Python, SQL, and common ML frameworks like PyTorch, XGBoost, etc * Strong communication and leadership skills; ability to influence roadmap and align cross-functional teams in a remote environment. * Proficiency and experience in applied statistics. Firm grasp of visualization tools, interactive and self-serving, such as dashboards and notebooks. * Preferred Qualifications: + Experience building ML applications for Discovery and Personalization domains + Experience with backend development ## Description * Lead the design, development, and productionization of ML models that power feed recommendations and buyer personalization * Lead ML-based projects from end-to-end: scoping and planning, data collection and feature engineering, model training and deployment, backend implementation, and online experimentation * Support product initiatives like exploration and international, new buyer, new seller, and small category growth. * Work closely with Backend Software Engineers to implement ML-based solutions into production. Contribute to backend development to support recommendations and feed work. * Drive technical excellence and establish ML best practices across the Buyer and Discovery teams, working closely with our Machine Learning Platform and Research teams. Grow ML knowledge across the team and support the scalability of our production models