5 days ago
San Francisco, CA, USAMid Level
Base Salary
$140k - $140k/yr
Responsibilities
- Design, train, and evaluate machine learning models for production use cases.
- Build end-to-end ML pipelines covering data preprocessing, model serving, and monitoring.
- Collaborate with product and engineering teams to develop ML solutions for business needs.
- Monitor, 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 teammates.
Requirements
- At least 3 years of professional experience in machine learning or software engineering, including hands-on production ML work and employment after graduation.
- A completed degree and experience in a substantive ML role at a product company or startup.
- Strong ML fundamentals in model selection, evaluation, feature engineering, and validation.
- Proficiency in Python and practical experience with TensorFlow, PyTorch, or scikit-learn.
- Experience building and maintaining production ML pipelines, including preprocessing, serving, and monitoring.
- Familiarity with MLOps and cloud tools such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.
- Experience with production A/B testing or experimentation and comfort working in fast-moving environments.
Benefits
- Starting salary of $140,000 USD annually.
- On-site work in San Francisco, California, United States.
- Equity and visa sponsorship details were not provided.