Machine Learning Platform Engineer
About the job
Truebill is a YC-backed startup with offices in San Francisco and Washington, D.C. Our DC office is right on the Silver Spring metro! Hundreds of thousands of people use Truebill to manage their daily finances and take control of their money. We just recently announced our $45m Series D round of funding and are now looking to scale our all star team in the DC Area!
With a mission to improve the financial health of everyday people, Truebill is transforming the way people manage their expenses and grow their net worth. Through helping people cancel unnecessary subscriptions, negotiating bills, and securing refunds, we save our members money while helping them regain control over their finances.
The interface between even the most robust ML systems and production systems is never a perfect transition. The data team at Truebill is looking for an ML Platform Engineer to join the growing ML team. This role will focus on bringing the value of our ML systems to our product. This means the next generation of overdraft prediction, a best in class transaction classification system, or the newest version of Autopilot to help our members take control of their finances and improve their financial wellness. You will not only help build the system, but design and build the interface between the Truebill product and the ML systems that power it, automating and building tooling to enable scale.
ABOUT THE ROLE
In this role, you will:
- Build the interfaces between our production ML systems and our production app, including: monitoring, integration tests, and feedback loops that allow our systems’ continuous improvement
- Design and build robust feedback loops for collecting member feedback and incorporating that into our production ML systems in a deliberate, curated way
- Work with Data Scientists, ML engineers, and ML operations to deliver predictions to our product and integrate them with software engineers in a robust, scalable and observable way
- Design, build, and lead adoption of tooling to enable both expert and non-experts a way to introspect and interpret our models and their performance – allowing us to test offline as well as analyze performance and monitor for drift in the online environment
- Work with data engineering, ML engineers, and data scientists as a stakeholder in the design and construction of our feature store to enable standardization and scale of our ML systems throughout the product
- 3+ years of production experience building systems that interface with or consume the output of ML systems and familiarity with both the full stack and ML stack of the product
- Practical experience operating ML products including monitoring, tuning, and collection of feedback data
- Experience with current ML tooling and willingness to learn and test new frameworks best suited to the problem
- Strong opinions on how to instrument ML models and their outputs that ensure quality predictions are being delivered to our users
- Prior experience with financial data, time series predictions, and transformer models is highly desired
- Health, Dental & Vision Plans
- Competitive Pay
- Matching 401k
- Unlimited PTO
- Lunch daily
- Snacks, Kombucha & Coffee on tap
- Commuter benefits
Truebill, Inc. is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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