Responsibilities
- Design, build, and operate scalable machine learning systems used in real-time targeting, decisioning, personalization systems
- Own ML projects end-to-end, from data exploration and modeling to deployment, monitoring, and iteration
- Proactively safeguard model and system quality through testing, monitoring, validation, and alerting
- Collaborate cross-functionally with product, data, and other engineering partners to translate business problems into ML solutions
- Continuously improve system reliability, performance, and engineering efficiency
- Contribute to technical direction and best practices across the ML engineering team
- Mentor and support other engineers through code reviews, design discussions, and knowledge sharing
- Thrive in a high-impact, fast-paced, late-stage startup environment
Requirements
- 6+ years of professional experience building production machine-learning software systems
- Proven experience owning ML systems long enough to see the downstream impact of design decisions
- Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or xgboost
- Experience with data processing and analytics tools such as pandas, Spark, SQL, and matplotlib
- Hands-on experience building automated pipelines for data processing, model training, validation, and deployment
- Experience collaborating with cross-functional teams to deliver ML-powered features
- Strong communication skills and a high sense of ownership
Benefits
- competitive perks and benefits
- health & wellness
- equity
