About this role
About the Role
As a Machine Learning Engineer, you'll build and deploy production machine learning systems for an AI-powered recruiting platform. You'll work across the ML lifecycle, partnering with product and engineering to turn business needs into reliable models and features.
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.
- 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.
What We're Looking For
- 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, including 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.
Compensation & Benefits
Salary starts at $140,000 USD annually. Equity and visa sponsorship details were not provided.
Location
On-site in San Francisco, California, United States.