Machine Learning Engineer

About Kalepa: Commercial insurance is a trillion-dollar industry run out of Microsoft Outlook. Kalepa is upending this. 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 " truly an underwriter's dream " and proclaim that Copilot helps them " almost double the amount of accounts they can look at in the day. " 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. 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). 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 Kalepa is looking for a Machine Learning Engineer with 2 years of experience to lead the framing, development, and deployment at the scale of machine learning models. As a MLE, you will own projects from 0 to 1 as we launch new features and enrich the underwriting process with valuable insights. The team works in two-week sprints and delivers 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. Tech Stack Back End: Python Development process: pSQL, RedShift, Jira, Docker What you will be responsible for: Turning vast amounts of structured and unstructured data from many sources (web data, geolocation, satellite imaging, etc.) into novel insights about behavior and risk Work closely with a small team designing, building, and deploying machine learning models to tackle our customers' questions Collaborate with a small team of full-stack, data, and DevOps engineers Apply to us if you have: Minimum of 2 years of experience An in-depth understanding of applied machine learning algorithms, especially NLP, and statistics Experience in Python and its major data science libraries and have deployed models and algorithms in production Comfort with data science and the engineering required to bring your models to production Experience with AWS (nice-to-have) Hands-on experience with data analytics and data engineering (nice to have) Excitement about using a comprehensive set of technologies, ultimately focused on finding the right tool for the job Preference for an open, frank, and respectful communication style Benefits: Very competitive base salary Significant equity options package (learn more https://carta.com/blog/equity-101-stock-option-basics/ ) 20 paid vacation days a year Paid Bank Holidays Unlimited Sick Leave (parental leave) Gym Reimbursment LuxMed comprehensive package Mobile phone bill reimbursement Continued learning Quarterly teams offsites in global locations Recruitment process in 10 quick steps - complete within 1-2 weeks (yes, not the shortest, but if you love challenges, you're in the right place. To reward that, you will always get clear & honest feedback within 24h top ) APPLICATION Apply via the link and send us your CV (in English) VERIFICATION Within 24h, our recruiter will verify your CV and reach out to you TASK Based on your preference, we will send a task on the HackerRank platform - 3 tasks, 75 min to complete you can choose a programming language PRELIMINARY CALL 30-minute conversation with a recruiter - you will learn more about the company and our culture & we will learn more about you TECHNICAL PHONE INTERVIEW 1h hands-on coding task with one of our Engineers CULTURE FIT INTERVIEW 30-minute meeting to measure if you are a good match for our organization FACE-TO-FACE STAGE 2h back and forth interview session. It contains 1h meeting about Data Science two 30-minute meetings during which you will meet our PM/Chief of Staff & CEO REFERENCES Uff, you are almost there As part of our process, we hold 2-3 reference calls with individuals who have worked with you in the past OFFER We will send you a proposal of the offer and await your decision. WELCOME You will write code from day one Daria will take care of your recruitment process If your expectations identify with ours and you want to join our team - apply today