Robinhood

Machine Learning Engineer, Applied ML

2 months agoMenlo Park, CA

Join a leading fintech company that’s democratizing finance for all.

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.

Just as we focus on our customers, we also strive to create an inclusive environment where our employees can thrive and do impactful work. We are proud of the competitive products and company culture we continue to build and have been recognized as:

  • Glassdoor Best Places to Work 2020
  • TIME100 Most Influential Companies 2021
  • Fortune Best Workplaces in Financial Services & Insurance™ 2021 and Fortune Best Workplaces for Millennials™ 2021

We’re growing and looking for...

We continue to hire Robinhoodies at a rapid pace to drive this journey, and with that growth comes necessary change. We’re seeking culture builders and curious thinkers looking to co-author the next chapters of our story. We’re in build mode, majorly expanding our team while also growing up as a company. Joining now means helping shape our structures and systems, then taking part as we launch into our ambitious future.

Check out life at Robinhood on The Muse!

About the role

Insights from data power most decisions at Robinhood. The Core ML team works with a simple mission of making it easy to use machine learning at Robinhood. The team is executing the mission by building the core infrastructure (eg. training and serving platform, feature platform) and a number of model-as-a-service solutions (eg. embedding service, multi-arm bandit service). The team works closely with data scientists who are applying ML in various spaces such as risk and fraud, growth, customer understanding etc. to ensure that they are able to ship their solutions to create business value.

As a machine learning engineer focused on applied ML, you will work closely with other teams to identify critical problems that can be solved using ML. You will co-develop a model, sometimes an ML system, with them and then, whenever possible, build and deploy the solution as a reusable and generalizable ML service. You will continue to build such services and onboard new applications to existing services over time.

What you’ll do day to day:

  • Dive into data to understand business problems that may benefit from ML
  • Train novel machine learning models and take them to production
  • Invest in feature engineering and model hyper-parameter tuning to improve predictive power and performance of the models
  • After deployment, closely monitor the model and take recourse to model interpretability to understand how its impacts on users
  • Work cross-functionally with data scientists, product managers, operations, and other engineering teams to build generalizable and reusable models
  • Collaborate with our data infrastructure teams to build highly scalable services and systems
  • Present ML success stories to internal and external audiences
  • Survey the latest and greatest in various areas of ML and bring the benefits of those to the firm whenever possible

About you:

  • MS/PhD and 2+ years of industry experience as Machine Learning Engineer preferred
  • Bachelors and 5+ years of industry experience as Machine Learning Engineer preferred
  • Solid understanding of machine learning and deep learning algorithms
  • Experience of working with large, noisy and highly imbalanced datasets
  • Experience of building and shipping ML models that are aligned with product roadmap
  • Excellent programming skills, including proficiency in Python and/or Go
  • Passion for working and learning in a fast-growing company
  • Excellent communication skills to tell a story through data.
  • Experience of building relationships and influencing stakeholders across multiple discipline

Bonus points:

  • Industry experience of delivering business impact with ML models or systems
  • Research and publication experience in any field of machine learning
  • Proof of excellence in Kaggle or similar forums

Technologies we use:

  • Python
  • Go
  • Scikit-learn
  • Tensorflow or Pytorch
  • Kubernetes
  • Kafka

We’re looking for more growth-minded and collaborative people to be a part of our journey in democratizing finance for all. If you’re ready to give 100% in helping us achieve our mission—we’d love to have you apply even if you feel unsure about whether you meet every single requirement in this posting. At Robinhood, we're looking for people invigorated by our mission, values, and drive to change the world, not just those who simply check off all the boxes.

Robinhood promotes diversity and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone. Additionally, Robinhood provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review Robinhood's Privacy Policy please visit rbnhd.co/applicant-privacy.

Robinhood's benefits include generous time off, 401(k) participation with employer match, comprehensive health coverage, a health savings account (HSA), wellness benefits, backup childcare and education stipends (all benefits are subject to applicable taxes and based on eligibility).