Machine Learning Engineer at Robinhood
🇺🇸 United States › California › Menlo Park (Posted Feb 10 2021)
About the company
Robinhood is democratizing finance for all. With customers at the heart of our decisions, Robinhood is lowering barriers, removing fees, and providing greater access to financial tools and information. Together, we are building products and services that help create a financial system everyone can participate in.
Robinhood is a fast-growing company and was recognized as a CNBC Disruptor 50 and a LinkedIn Top Startup in 2019. We’re continuing to grow and are looking for incredible talent that can help us achieve our mission.
Machine Learning Engineer, CX Understanding
About the Role
Our team’s mission is to continuously improve the customer experience through data driven insights, experimentation, machine learning, and natural language processing technologies. We are looking for machine learning engineers who will build, deploy and monitor machine learning tools and models to improve our customer’s experience with predictive solutions.
Your day-to-day will involve:
Design, train and deploy machine learning and/or natural language understanding models
Design and implement new features for our feature store and engineer real-time data pipelines to incorporate them into our models
Applying research and existing academic work to real-life problems
Writing production quality code, scaling solutions for high-throughput and low-latency requirements
Improving the way we evaluate and monitor our model and system performance
Evaluating models, optimizing for a variety of stakeholders (product, operations, compliance)
Collaborate with our product, design and user research partners as well as the data scientists and engineers in our team to design and architect innovative machine learning solutions to improve Robinhood’s customer experience
Some things we consider critical for this role:
3+ years of experience as machine learning engineer or applied machine learning scientist
Experience with machine learning pipelines and concepts such as large-scale training, batch feature extraction, real-time serving platforms
Experience with common ML/NLP libraries, such as NLTK, TensorFlow, Keras
Experience with machine learning techniques and advanced analytics (e.g. regression, classification, time series, causal inference, text analytics)
Experience working with datasets that reflect real life problems such as noisy, highly imbalanced datasets
Comfort conducting design and code reviews
Masters or PhD in machine learning or natural language processing
Passion for working and learning in a fast-growing company
Experience with impactful ML/NLP solutions for customer facing product problems
Experience with distributed data platforms, such as Spark or Kafka
Experience with ML deployment frameworks such as MLflow or Kubeflow
Feeling ready to give 100% to democratizing finance for all? 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, not just those who simply check off all the boxes.
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