Machine Learning Engineer (USA)

<div class="content-intro"><h2>About Kalepa:</h2>
<p>Commercial insurance is a trillion-dollar industry run out of Microsoft Outlook.</p>
<p>Kalepa is upending this.&nbsp;</p>
<p>Our state-of-the-art AI Copilot platform empowers underwriters to make smarter, faster, and more accurate decisions. Our AI is designed to deliver real results - insurers literally see massive improvements to their top and bottom lines as soon as they implement Copilot. That’s why our clients call Copilot “<a href="https://www.kalepa.com/case-study/cassie-paul-talks-about-copilot-driven-success-at-paragon-insurance">truly an underwriter’s dream</a>” and proclaim that Copilot helps them “<a href="https://www.kalepa.com/case-study/i-would-say-we-almost-double-the-amount-of-accounts-we-can-look-at-in-the-day">almost double the amount of accounts they can look at in the day.</a>"<a href="https://www.kalepa.com/case-study/i-would-say-we-almost-double-the-amount-of-accounts-we-can-look-at-in-the-day">&nbsp;</a></p>
<p>Kalepa's team members bring experience from top technology companies, including Facebook, Google, Amazon, Mastercard, and Uber. Kalepa is backed by leading VCs like IA Ventures and Inspired Capital.</p>
<h2>Our Values (This is important):</h2>
<p>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.&nbsp;</p>
<p>Success at Kalepa is bred from five core principles:</p>
<ul>
<li><strong>Hustle &amp; Grit</strong> - 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.</li>
<li><strong>Customer Focus</strong> - 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.</li>
<li><strong>Meritocracy</strong> - 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.&nbsp;</li>
<li><strong>Transparency </strong>- 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.</li>
<li><strong>Experimentation </strong>- 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.</li>
</ul>
<p>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).</p>
<p>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.&nbsp;</p></div><p><strong>Salary range: &nbsp;<span class="styles_compensation__DUzmb">$120k – $150k&nbsp;</span></strong></p>
<p><strong><span class="styles_compensation__DUzmb">Equity range: 0.03% – 0.15%</span></strong></p>
<p>&nbsp;</p>
<p><strong>What we are looking for:</strong></p>
<p>Kalepa is looking for a<strong>&nbsp;Machine Learning Engineer</strong> with 3<strong>+ years</strong> of experience to lead the framing, development, and deployment at the scale of machine learning models. <strong>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.</strong> 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.&nbsp;</p>
<p>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.</p>
<p><br><strong>About you:</strong></p>
<ul>
<li style="font-weight: bold;"><strong>You must have 3+ years of experience in engineering and data science.</strong></li>
<li>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.</li>
<li>You have in-depth understanding of applied machine learning algorithms, especially NLP, and statistics</li>
<li>You are experienced in Python and its major data science libraries, and have deployed models and algorithms in production</li>
<li>You are comfortable with data science as well as with the engineering required to bring your models to production.</li>
<li>You are excited about using a wide set of technologies, ultimately focused on finding the right tool for the job.</li>
<li>You value open, frank, and respectful communication.</li>
</ul>
<p><strong>As a plus:</strong></p>
<ul>
<li>You have experience with AWS</li>
<li>You have hands-on experience with data analytics and data engineering.</li>
</ul>
<p><strong>What you’ll get: </strong></p>
<ul>
<li>Competitive salary (based on experience level).</li>
<li>Significant equity options package.</li>
<li>Work with an ambitious, smart, global, and fun team to transform a $1T global industry.</li>
<li>20 days of PTO a year.</li>
<li>Global team offsites.</li>
<li>100% covered PPO medical, 100% covered vision and dental for individuals and families.</li>
<li>Healthy living/gym stipend. Mobile phone bill stipend.</li>
<li>Continuing education credits.</li>
<li>401(k) plan with employer contribution (regardless of employee contribution)</li>
</ul>
<p>&nbsp;</p>