Why This Role Stands Out
This role offers a fantastic opportunity to build and deploy impactful ML systems within a dynamic product environment, fostering significant career growth and skill development. If you thrive on end-to-end ML lifecycle challenges and enjoy collaborating to deliver innovative solutions, you'll find this position incredibly rewarding.
Quick Overview
Job Description
About the Role
Work on building and deploying ML systems that power a fast moving product. You will contribute across the full ML lifecycle and collaborate with product and engineering teams to ship models that make a real impact.
What You'll Do
Design, train, and evaluate machine learning models for production use cases.
Implement end to end ML pipelines from data preprocessing to model serving and monitoring.
Collaborate with product and engineering teams to translate business requirements into ML solutions.
Debug and optimize model performance in production and iterate based on real world feedback.
Write clean, maintainable code and contribute to ML infrastructure and tooling.
Participate in code reviews and share knowledge with the broader team.
What We're Looking For
3+ years of professional experience in machine learning or software engineering with hands on applied ML in production systems.
Experience in startup or fast moving product environments with rapid iteration cycles.
Strong fundamentals in model selection, evaluation, feature engineering and validation.
Proficiency in Python or similar languages and ML frameworks such as TensorFlow, PyTorch or scikit learn.
Experience building, deploying and maintaining ML systems at scale including A/B testing, monitoring, data pipelines and MLOps tools such as cloud ML platforms and container technologies.
Comfort with ambiguity and ability to prioritize impact in a dynamic setting.
Location
On site at our San Francisco, CA headquarters. Primary location: San Francisco, California, United States.