Staff Machine Learning Engineer

About the team + role

The Growth team is responsible for driving user & revenue growth for Robinhood. As we expand our suite of product offerings, we want to make sure we are taking a personalized approach to driving growth & engagement, by helping each user discover & engage with the right products & features within Robinhood that they might find most valuable. As we embark on this path, we are looking for a senior MLE to come in and lead our personalization efforts, and conceive, build & execute on a roadmap for how to effectively personalize our app experiences to drive user growth & engagement.

What You'll Do:

As a Machine Learning Engineer in our team, your primary focus will be on the implementation and evaluation of machine learning algorithms through rigorous experimentation and testing methodologies. Your responsibilities will include:

• Model Development and Implementation: Develop and fine-tune machine learning models, with a focus on ranking and scoring. Ensure these models are scalable and efficient.
• Development of Reinforcement Learning Models: Design and implement reinforcement learning algorithms to optimize decision-making processes in dynamic environments.
• 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.
• Multi-Armed Bandit Implementation: Apply multi-armed bandit strategies for real-time decision-making in our algorithmic processes. Balance the trade-off between exploration of new strategies and exploitation of known successful approaches.
• Bayesian Optimization Techniques: Utilize Bayesian optimization for hyperparameter tuning and model optimization. Focus on achieving higher efficiency in model selection and parameter optimization.
• 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 product managers 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 you bring

• 3+ years of applied ML experience productionizing ML models.
• 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.
• Practical and demonstrable experience with ML algorithms within the space of multi-armed bandits, search relevance, ranking, advertisement targeting, or reinforcement learning.
• Proficiency in Python, k8s, PyTorch, or TensorFlow2.
• Ideally you have experience in the Finance sector.
• Experience with SQL, Spark, Kafka, and Flink is also desirable.

What we offer

• Market competitive and pay equity-focused compensation structure
• 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!
• Lively office environment with catered meals, fully stocked kitchens, and geo-specific commuter benefits