The business is seeking to democratize finance for all by providing scalable data and model driven decision making solutions to the various business functions at Robinhood.
Requirements
- 5+ years of applied ML experience productionizing ML models with 2+ years focused on recommendations, ranking or personalization projects
- Proficiency in Python, SQL, XGboost, PyTorch/TensorFlow
- Experience with Spark, Kafka, and Kubernetes is also desirable
- Familiarity with architectural frameworks of large, distributed, and high-scale ML applications
- Proven experience in ML with a focus on ranking, recommendation systems, multi-objective optimization, and reinforcement learning
Responsibilities
- Develop and implement scalable machine learning models focusing on advanced ranking and recommendation systems
- Design and conduct A/B tests to assess the performance of different machine learning models
- Analyze experimental data to extract actionable insights
- Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product
- Build reusable libraries for common machine learning practices
- Maintain comprehensive documentation of libraries, models, experiments, and findings
Other
- 5+ years of experience
- Education, training, experience, location, business needs, or market demands may be considered for base pay
- Must be eligible to work in the US
- 100% paid health insurance for employees with 90% coverage for dependents
- Annual lifestyle wallet for personal wellness, learning and development, and more!
- Lifetime maximum benefit for family forming and fertility benefits
- Dedicated mental health support for employees and eligible dependents
- Generous time away including company holidays, paid time off, sick time, parental leave, and more!
