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Home›Jobs›Kalepa›Senior Machine Learning Engineer (Europe)
Kalepa

About Kalepa

Transforming commercial insurance with AI-driven insights

🏢 Retail👥 21-100 employees📅 Founded 2018📍 Flatiron District, New York, NY⭐ 4.9
FintechB2BArtificial IntelligenceInsurance

Key Highlights

  • Headquartered in Flatiron District, New York, NY
  • Reduces quote delivery time by over 40%
  • Saves businesses over $15M in losses annually
  • Offers significant equity options and aggressive bonuses

Kalepa is an AI-driven commercial insurance provider headquartered in the Flatiron District of New York, NY. The company utilizes a human-AI platform to help businesses identify their unique risks and secure tailored insurance coverage. With a focus on transforming the $1 trillion global insurance i...

🎁 Benefits

Kalepa offers excellent benefits including 100% covered medical, vision, and dental insurance, along with a very generous PTO policy. Employees can al...

🌟 Culture

Kalepa's culture is centered around leveraging AI to disrupt the traditional insurance landscape. The company values a data-driven approach to underwr...

🌐 Website💼 LinkedIn𝕏 TwitterAll 26 jobs →
Kalepa

Senior Machine Learning Engineer (Europe)

Kalepa • Europe (Full Remote)

Posted 1 month ago🏠 RemoteSeniorMachine learning engineer📍 Europe
Apply Now →

Job Description

About Kalepa:

Commercial insurance is a trillion-dollar industry still run out of Microsoft Outlook.

Kalepa is changing that.

Kalepa is an AI Underwriting Platform built to deliver Professional-Grade AI in production - helping the world's most important insurers centralize and prioritize submission data, surface critical risk insights, and make faster, more confident decisions. Customers see meaningful improvements to both speed and portfolio quality as soon as they implement Kalepa - so much so that clients call it “truly an underwriter’s dream.”

Kalepa is backed by leading investors such as IA Ventures and Inspired Capital, and our team brings experience from Facebook, Google, Amazon, Mastercard, and Uber.

Our Values (This is important):

Many organizations have a dusty list of corporate values that no one ever follows. Kalepa is not one of those companies. Our values are designed to unlock the potential of our employees. 

Success at Kalepa is bred from five core principles:

  • Hustle & Grit - We expect everyone at Kalepa to be excellent at what they do and relentless in pursuing their craft. There are no easy days. Kalepa’s exceptional speed and determination are our biggest differentiators: this is how we win.
  • Customer Focus - We will ruthlessly prioritize the work that drives our clients’ growth, profitability, and efficiency. We are not building things just because they seem cool - we are here to solve our customers’ most strategic problems.
  • Meritocracy - Too many exceptional people are stifled by corporate bureaucracies. At Kalepa, those people excel - and we reward tremendous results with rapid promotions and compensation growth. 
  • Transparency - We are honest with each other. We don’t believe in back-office politics and keeping employees in the dark. Transparency allows us to instantly cut to the heart of the matter and figure it out together.
  • Experimentation - For many of the problems we face, no company has ever solved them before. We tackle these by quickly testing, measuring, and iterating to determine the path to success.

In addition to our NY office, we have remote employees speaking 10+ languages across the globe. But we invest in bringing our people together both for regional meetups and global offsites (2021 - Playa Del Carmen | 2022 - Rome | 2023 - Buenos Aires | 2024 - Lisbon | 2025 - Cartagena).

Kalepa’s culture isn’t for everyone, and that’s ok. But for the people who are a fit, they can’t imagine working elsewhere. 

About the role:

Salary range: $85k – $165k USD*

 

Kalepa is looking for a Senior Machine Learning Engineer with 5+ years of experience to lead the framing, development, and deployment at the scale of machine learning models. As a 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. 

Team members are given full ownership over their projects and are expected to drive the project’s direction and maintain focus. The team works in a two-week sprint, and ML Engineers will work closely with Product Management and Software Engineers.


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.
  • 20 days of PTO a year.
  • Global team offsites.
  • Phone reimbursement. Gym reimbursement.
  • Student stipend. 

*The salary range listed is an estimate and will vary based on a variety of factors. Final compensation will be determined during the offer stage based on relevant experience, performance during the interview process, and geographic location, and may therefore differ from the posted range. 

Interested in this role?

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