5 hours ago
San Francisco, CA, USAMid Level
Responsibilities
- Design, train, and evaluate machine learning models for production use cases.
- Implement end-to-end ML pipelines for data preprocessing, model serving, and monitoring.
- Partner with product and engineering teams to translate business requirements into ML solutions.
- Debug and optimize production model performance using real-world feedback.
- Write maintainable code and contribute to ML infrastructure and tooling.
- Participate in code reviews and share knowledge with the broader team.
Requirements
- At least 3 years of professional experience in machine learning or software engineering, including hands-on experience building and deploying production ML systems.
- Proficiency in Python and experience with at least one of TensorFlow, PyTorch, or scikit-learn.
- Experience implementing end-to-end ML pipelines, including preprocessing, model serving, and production monitoring.
- Strong ML fundamentals in model selection, evaluation metrics, feature engineering, and validation techniques.
- Experience deploying and maintaining ML systems with MLOps tools or cloud platforms such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.
- Experience with A/B testing or experimentation frameworks in production environments.
- Background in startup or fast-moving product environments with rapid iteration cycles.
- Ability to work comfortably with ambiguity and prioritize for impact.
Benefits
- The role is on-site in San Francisco, California.