Machine Learning Engineer (Mid-Level)

### **About the Role** Build and deploy production machine learning systems in a fast-moving product environment. You will own work across the ML lifecycle, partnering with product, engineering, and domain experts to deliver models that address real business needs. ### **What You'll Do** * Design, train, and evaluate machine learning models for production use cases. * Build end-to-end ML pipelines, from data preprocessing through model serving and monitoring. * Work with product and engineering partners to turn business requirements into ML solutions. * Debug and improve production model performance using monitoring data and real-world feedback. * Write maintainable code and contribute to ML infrastructure and tooling. * Participate in code reviews and share technical knowledge with teammates. ### **What We're Looking For** * At least 3 years of professional machine learning or software engineering experience, including hands-on ownership of production ML systems in a startup or fast-moving product environment. * Strong ML fundamentals, including model selection, evaluation, feature engineering, and validation. * Proficiency in Python and hands-on experience with TensorFlow, PyTorch, or scikit-learn. * Experience implementing production ML pipelines that cover data preprocessing, model serving, and monitoring. * Experience deploying and maintaining ML systems at scale with tools or platforms such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker. * Experience with production A/B testing or experimentation frameworks, and optimizing models based on results. * A completed university degree and professional employment experience after graduation. * Ability to work through ambiguity and prioritize practical impact in a dynamic environment. ### **Location** On-site in San Francisco, California.