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Senior Machine Learning Engineer (USA)

Kalepa is an award-winning AI software company transforming the trillion-dollar commercial insurance industry. Our state-of-the-art AI Copilot platform empowers underwriters to make smarter, faster, and more accurate decisions, so insurers can grow their top and bottom lines while business owners get the coverage they need.Copilot is delivering real, tangible impact to insurers from day 1, and underwriters rave about it. . "[They] don't know if [they] could function doing daily underwriting without having it." and they assert that "not only is Kalepa's technology miles ahead of other vendors, but when it came to driving real impact on our business, there [is] no competition."Kalepa's Copilot powers insurers of all sizes, including +$10B carriers like Arch and Munich Re, hypergrowth MGAs like Bowhead Specialty and Paragon, and small regional insurers like North Star Mutual.At Kalepa, you'll join a team of doers who are passionate about innovating and winning. We are a fast-moving group with high expectations for every person we hire and everything we build.Join us if you want to be a crucial part of a company whose AI actually works.Salary range: $140k - $190kEquity range: 0.01% - 0.15%What we are looking for: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.• 100% covered PPO medical, 100% covered vision and dental for individuals and families.• Healthy living/gym stipend. Mobile phone bill stipend.• Continuing education credits.• 401(k) plan with employer contribution (regardless of employee contribution)Kalepa's team members bring experience from top technology, including Facebook, Google, Amazon, Mastercard, and Uber. 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.
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Paul Monasterio
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Kalepa is the leader in delivering Efficient Frontier commercial insurance. Insurers find it difficult to understand the true exposures of businesses and to profitably provide them with policies that reflect that true risk. SMBs struggle to find ...

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Full-time, on-site
DATE POSTED
July 3, 2024

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