Machine Learning Engineer (Mid-Level)

About the Role Join a small, fast-moving team building AI-powered talent and recruiting technology. You will design, deploy, and maintain machine learning systems across the full lifecycle, helping turn product needs into reliable production capabilities. 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 translate business requirements into ML solutions. - Debug and improve models in production using monitoring data and real-world feedback. - Write maintainable code and contribute to ML infrastructure and tooling. - Participate in code reviews and share knowledge with teammates. What We're Looking For - A degree and at least 3 years of professional machine learning or software engineering experience, including building and deploying production ML systems. - Strong understanding of model selection, evaluation metrics, feature engineering, and validation techniques. - Proficiency in Python and hands-on experience with TensorFlow, PyTorch, or scikit-learn. - Experience implementing production pipelines for data preprocessing, model serving, and monitoring. - Experience 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. - Background working in fast-moving product environments and iterating on ML systems based on production feedback. Compensation & Benefits Base salary: $140,000 USD annually. Visa sponsorship information was not provided. Location On-site in San Francisco, California, United States.