Kalepa is looking for Machine Learning Engineers with 2+ 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 be working closely with a small team in designing, building, and deploying machine learning models to tackle our customersā questions. You will be collaborating 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 donāt 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.
About you:
- You love to hustle: finding ways to get things done, destroying obstacles, and never taking no for an answer. The words āit canāt be doneā donāt 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 youāll get
- Very competitive base salary plus significant number of stock options on top of that (you can learn more about options at
- Paid 20 vacation and personal days a year
- Mobile phone bill reimbursement plan up to
- Multisport Plus Card, LuxMed comprehensive package
- Continuing education credits up to, home office stipend up to
- Quarterly teams offsites in global locations
- Work with an ambitious, smart, global, and fun team to transform a $1T global industry.
- Ground floor opportunity ā opportunity to build the foundations for the product, team, and culture alongside the founding team.
- Wide-ranging intellectual challenges spanning full-stack software development, AI / ML, and strong design.
- Assistance with getting the 5% tax rate on your base salary (IP BOX).
- Fully remote working environment.
Natural language processing (NLP) Data Analyst Python Machine Learning Amazon Web Services (AWS) Data Engineering