Role overview
Robinhood was founded on a simple idea: that our financial markets should be accessible to all. With customers at the heart of our decisions, Robinhood is lowering barriers and providing greater access to financial information. Together, we are building products and services that help create a financial system everyone can participate in.
As we continue to build...
Weâre seeking curious, growth minded thinkers to help shape our vision, structures and systems; playing a key-role as we launch into our ambitious future. If youâre invigorated by our mission, values, and drive to change the world â weâd love to have you apply.
What you'll work on
- Model Development and Implementation: Develop and implement scalable machine learning models focusing on advanced ranking and recommendation systems, including expertise in Collaborative Filtering, Content-Based Filtering, and Hybrid models, alongside proficiency in Learning to Rank (LTR) techniques for effective prioritization. Additionally, design reinforcement learning algorithms and apply multi-armed bandit strategies to optimize decision-making in dynamic environments, balancing exploration and exploitation.
- A/B Testing and Experimentation: Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance, and analyzing results.
- Data Analysis and Insight Generation: Analyze experimental data to extract actionable insights. Use statistical techniques to validate the findings and ensure their relevance and accuracy.
- Cross-Functional Collaboration: Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements.
- Documentation and Reporting: Maintain comprehensive documentation of models, experiments, and findings. Prepare reports and presentations to communicate results to different stakeholders.
What we're looking for
- 5+ years of applied ML experience productionizing ML models with 2+ years focused on recommendations, ranking or personalization projects.
- A fervent interest in exploring and applying AI and ML technologies.
- Strive to solve sophisticated engineering problems that drive business objectives.
- Solid technical foundation enabling active contribution to the design and execution of projects and ideas.
- Familiarity with architectural frameworks of large, distributed, and high-scale ML applications.
- Proven experience in ML with a focus on ranking, recommendation systems, and reinforcement learning, including applications in targeted advertising.
- Expertise in leveraging diverse communication platforms, such as email campaigns, push notifications, and in-app promotions.
- Proficiency in Python, SQL, PyTorch, or TensorFlow.
- Experience with Spark, Kafka, and Kubernetes is also desirable.
- Ideally you have experience in the Finance sector.
Tags & focus areas
Used for matching and alerts on DevFound Machine Learning Ai Engineer Senior Kubernetes Tensorflow Pytorch Python Spark