We're looking for a software engineer at heart who can flex into ML engineering territory for a great mission! (remote in San Francisco, Los Angeles, Seattle)
About the job
What We Do
Pave delivers AI-powered analytics and scores about a borrower’s cashflow and affordability. We’re an early-stage startup on a mission to enable equitable financial access for every American.
50+ risk teams use Pave to reduce defaults, provide the optimal loan amount/credit limit, and maximize collections success.
Pave is backed by Better Tomorrow, Ark Invest, Alumni Ventures, and other top funds and angels from Coinbase, Chime, SoFi, CashApp, and Plaid.
Who You Are
- You pride yourself on having a strong product mindset.
- You channel your energy towards understanding and solving your customers' problems.
- You are an engineer who loves to build high-quality software.
- You are also a numbers person, with a passion for data, analytics, and modeling.
- You understand that ML is only one tool among many others.
- You know when to use ML and when not to.
- You are not afraid to launch and improve a product without ML.
- You understand that .fit() is only the tip of the iceberg, and you’ve been underwater.
- You are "full stack" and can go all the way from reading a paper, labeling data, experimenting with a prototype, to building data pipelines and shipping to production.
- You have very high-quality standards, but you also know how to move fast.
- You appreciate the significant impact great financial products can have on people’s lives.
- You are hungry and want to work at an early-stage startup and win.
The Role
At Pave, you will have the opportunity to develop the foundational models and APIs the next generation of fintech startups are being built upon. We’re constructing the insights, predictions, attributes and scores layer that enables risk teams to harness raw fintech data sources to identify healthy borrowers, optimize credit limits and improve collection outcomes.
We’re looking for an ML Engineer with strong skills in engineering, modeling, data and analytics. You'll report directly to the Director of Engineering. You’ll be expected to take ownership of a variety of areas. You will rapidly become an expert and a champion on key topics that the rest of the team can rely on. You will lead your own projects and drive direct business value.
Our Stack
- Python
- AWS
- S3 (we use it as our main data backend)
- Snowflake
- Scikit Learn
- Gradient-boosted Trees
- Weights & Biases
- Kubernetes
- Dagster
- Postgres
- Kafka
- Terraform
- Github
- Github Actions
- Datadog
- Sentry