Full-Time Machine Learning Engineer IV
Job Description
Want to help everyday Americans build wealth? Financial inequality is increasing and too many people are getting left behind. At Stash, we believe in the power of simplifying investing, making it easy and affordable for everyday Americans to build wealth and achieve their financial goals.
We’re one of the fastest growing fintechs in the U.S. and have had another record-breaking year. In 2021 we almost doubled our headcount and valuation. Our personal finance app makes investing easy and affordable; this year 6 million customers set aside more than $3 billion with Stash.
Prioritizing People is one of our core values and has been key to a healthy work-life balance and a great sense of fulfillment and inclusion. We employ a true people first – hybrid model. Live and work where you feel the most productive, whether that is in your home, in an office, or a combination of both. Anywhere in the US or UK.
Let’s solve complex problems and tackle wealth inequality.
Stash is seeking a Senior Machine Learning Engineer to join our engineering team. This role focuses on shipping ML-driven features that enhance the steady building of wealth, spend management and financial education for millions of our customers.
As a ML engineer, you will work across many functions in the company from Design, Modeling, Engineering, Growth, Support and Fraud Prevention to enable sophisticated AI solutions at scale. We are looking for technical professionals with motivation and deep knowledge to build beautiful, intuitive products with empathy for our customers. This is a career-defining opportunity, where you will join one of the fast-growing fintech companies and help bring to market the latest innovations including crypto products.
You will:
- Formulate a real-world enterprise scenario into a machine learning problem and design the optimal solutions for the problem.
- Wrangle with large data sets on the cloud and transform them into innovative features/signals to improve a machine learning model.
- Participate in end-to-end machine learning lifecycle, from prototyping, implementation & evaluation ML and DL models, followed by deployment and monitoring using cloud tools.
- Develop entity graphs, feature stores, model training and model serving capabilities in a fault-tolerant distributed computing environment
- Collaborate with other ML engineers and Data Scientists in building highly scalable ML models for NLP, Fraud Prevention, Growth, Recommenders, Personalization and other use cases
- Understand industry and company-wide trends to help develop new technologies
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Applied Mathematics, or related fields
- 5+ years of experience (or research projects in lieu of industry experience) in the areas of machine learning, data science, or information retrieval
- Proficiency and demonstrable skills in programming languages (Python, C++, Java or related ML programming languages)
- Experience with cloud computing platforms, such as AWS, Google Cloud or Azure
- Eagerness to share your own ideas, and openness to those of others
**No recruiters please**
How to Apply
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