Machine Learning Engineer (USA)
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: $85k – $125k
Equity range: 0.005% – 0.025%
What we are looking for:
Kalepa is looking for Machine Learning Engineers with 3+ years of experience to frame, develop and deploy at-scale of machine learning models to understand the risk of various classes of businesses. We are a fully remote startup building software to transform and disrupt commercial insurance. Our HQ is located in New York.
In this role, 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. You will work closely with a small team designing, building, and deploying machine learning models to tackle our customers’ questions. You will collaborate with a small team of full-stack, data, and DevOps engineers.
Every business on the planet needs insurance. Nearly one trillion ($1T) dollars are spent globally each year on commercial insurance to protect businesses from fires, injuries, lawsuits, etc. However, commercial insurance is plagued with a big problem. Businesses and insurers don’t trust each other. This leads to a lot of economic waste. Missed opportunities, mispricing, and mistakes. Everyone is worse off.
By combining cutting-edge data science and a proprietary learning engine in a delightful-to-use software platform, Kalepa is solving this problem and turning every underwriter into a top underwriter. There are many challenging technical problems as we continue to build and expand our software -- and a massive opportunity to transform an ancient industry that comprises 6% of world GDP.
Kalepa's team members bring experiences from Facebook, Google, Amazon, ClassPass, Atlassian, Mastercard, MIT, Berkeley, UPenn, the University of Warsaw, and the Israel Defense Forces.
Kalepa is backed by IA Ventures, lead early-stage investors on TheTradeDesk (IPO, $38B valuation), Datadog (IPO, $32B), TransferWise (last valued at $5B), DataRobot ($2.7B), Flatiron Health (acquired for $2B), and several other unicorns and public companies.
- 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.
- 100% covered PPO medical, 100% covered vision and dental for individuals and families.
- 20 days of PTO a year.
- Healthy living/gym stipend. Mobile phone bill stipend.
- Continuing education credits.
- Home office stipend.
- 401(k) plan with employer match.
- Global team offsites.