Kalepa is an award-winning software start-up re-imagining the trillion-dollar commercial insurance industry. Our cross-functional teams leverage AI, cutting-edge tech, and tons of data to help commercial insurance underwriters Bind with Confidence.
Why We're Here:
For hundreds of years. businesses have tried to find the right policy to protect themselves and their employees. However, commercial insurance is plagued with a big problem: it's really complicated!
Insurers find it hard to understand the true exposures of businesses and to profitably provide them with policies that reflect that risk. Businesses - like contractors, hotels, restaurants, transportation fleets, real estate lessors, and others - struggle to find the coverage they need and are often left underinsured, uninsured, or paying too much for what they need.
That's where we come in. Our AI-powered underwriting workbench - Copilot - compiles everything underwriters need, and flags the exposures they need to know about. With Copilot, underwriters can find critical information in a flash; digitize their underwriting guidelines; triage, prioritize, and track their book; and automatically read and summarize key documents, like loss runs and supplemental applications – all out of the box. This means that insurance carriers grow faster and are more profitable, and businesses get the right coverage at the right rates. It’s the way insurance should work.
Salary range: $140k – $190k
Equity range: 0.01% – 0.15%
What we are looking for:
As a Senior Machine Learning Engineer you will lead the framing, development, and deployment at scale of machine learning models to understand the risk of various classes of businesses. You will be turning vast amounts of structured and unstructured data from many sources (web data, geolocation, satellite imaging, etc.) into novel insights about behavior and risk.
Kalepa's team members bring experience from top technology, insurance, and intelligence institutions including Facebook, Google, Amazon, Uber, Doordash, Mastercard, Chubb, AIG, Zurich, Everest Insurance, MIT, Berkeley, UPenn, and the Israel Defense Forces.
Kalepa is backed by IA Ventures (early investors in Datadog, Wise, Better, Digital Ocean, TheTradeDesk, Flatiron Health, Komodo Health, etc.), Former Secretary of Commerce Penny Pritzker’s Inspired Capital, and leaders in financial services and technology including Gokul Rajaram from Doordash, Coinbase, and Square, Jackie Reses from Square, Affirm, and Alibaba, and Henry Ward from Carta.
In July 2021 we raised a $14 million Series A funding round led by Inspired Capital, with participation from previous investor IA Ventures.
About you:
- You have 5+ years of experience in engineering and data science.
- You love to hustle: finding ways to get things done, destroying obstacles, and never taking no for an answer. The words “it can’t be done” don’t exist in your vocabulary.
- You have in-depth understanding of applied machine learning algorithms, especially NLP, and statistics
- You are experienced in Python and its major data science libraries, and have deployed models and algorithms in production
- You are comfortable with data science as well as with the engineering required to bring your models to production.
- You are excited about using a wide set of technologies, ultimately focused on finding the right tool for the job.
- You value open, frank, and respectful communication.
As a plus:
- You have experience with AWS
- You have hands-on experience with data analytics and data engineering.
What you’ll get:
- Competitive salary (based on experience level).
- Significant equity options package.
- Work with an ambitious, smart, global, and fun team to transform a $1T global industry.
- Ground floor opportunity – an early member of Kalepa’s engineering leadership team
- 20 days of PTO a year.
- Global team offsites.
- 100% covered PPO medical, 100% covered vision and dental for individuals and families.
- Healthy living/gym stipend. Mobile phone bill stipend.
- Continuing education credits.
- Home office stipend.
- 401(k) plan with employer match.
