Machine Learning Engineer (USA)

September 7

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Kalepa

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Your Underwriting Copilot

Insurance • Data • Analytics • Commercial Insurance • Specialty Insurance

11 - 50

💰 $14M Series A on 2021-09

Description

• Kalepa is looking for a Machine Learning Engineer with 3+ years of experience to 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.

Requirements

• You must have 3+ 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. • You have experience with AWS. • You have hands-on experience with data analytics and data engineering.

Benefits

• 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).