<p><span style="font-weight: 400;"><strong>Narvar</strong> is growing! We are hiring a Staff Software Engineer to build new products and improve all aspects of the Narvar platform. Data is at the core of our competitive advantage so the work you do has a large impact across the company, our business partners, and the lives of our end users.</span></p>
<p><span style="font-weight: 400;">Machine Learning Engineers at Narvar work across the stack. We are ‘full-stack’ ML Engineers. This means that we write production-level code and own machine learning operations for our teams. </span></p>
<h4><strong>Day-to-day</strong></h4>
<ul>
<li style="font-weight: 400;"><span style="font-weight: 400;">Design and deploy machine learning algorithms for use cases spanning e-commerce, consumer trends, markets, logistics, and new products</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Work on real-world consumer data for natural language processing, image classification, time series analysis, outlier detection, user modeling, etc</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Work with large unstructured data</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Be at the intersection of mathematics, machine learning, business, and computer science and impact millions of users through your work</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Multiply the effect of your data science and data team members by building frameworks, tools, and methodologies that the entire team use </span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Provide thought leadership to a team through high quality write-ups, reviews, and a strong vision grounded in practical experience and a wider industry view</span></li>
</ul>
<h4><strong>What we’re looking for</strong></h4>
<ul>
<li style="font-weight: 400;"><span style="font-weight: 400;">Strong machine learning skills. </span></li>
<li><span style="font-weight: 400;">Fluency in Python, PyTorch, Tensorflow, Pandas, numpy, and machine learning packages</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Data Engineering skills and large data experience. You should have dealt with large amounts of data (TB) in a production setting, built world class data pipelines using cutting edge tools (e.g. Spark).</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;"> 5+ years of hands-on experience shipping models to production, working on a variety of problem spaces (eg: user modeling, spam classification, prediction, clustering etc)</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">MS in Computer Science, Statistics, Math, Science (physical or social), Engineering or similar quantitative and computation field plus 5+ years of industry experience</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Strong software engineering and coding skills with the ability to write production quality code</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Strong understanding of probability & statistics, machine learning, and algorithms</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Experience with SQL and NoSQL databases</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Experience working with Linux, shell scripting</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Previous startup experience strongly preferred</span></li>
</ul>
<h4><strong>Bonus Points</strong></h4>
<ul>
<li><span style="font-weight: 400;">Experience implementing applications on Google Cloud Platform</span></li>
<li><span style="font-weight: 400;">Experience with deep generative models or graph learning a plus.</span></li>
<li><span style="font-weight: 400;">Tag your application with your solution to an active / recently concluded Kaggle competition, to get ahead of the list :)</span></li>
<li><span style="font-weight: 400;">Experience leading a team of data and data scientists; Strong ability to multiply the effect of the team and the team members; excellent written communication; self-starter that can balance sophistication with practicality</span> </li>
</ul>
<h4><strong>Why Narvar?</strong></h4>
<p><span style="font-weight: 400;">We're on a mission to simplify the everyday lives of consumers. Post-purchase is a critical phase of the customer journey. That's why we created Narvar - a platform focused on driving customer loyalty through seamless post-purchase experiences that allow retailers to retain, engage, and delight customers. If you've ever bought something online, there's a good chance you've used our platform!</span></p>
<p><span style="font-weight: 400;">From the hottest new direct-to-consumer companies to retail’s most renowned brands, Narvar works with GameStop, Neiman Marcus, Sonos, Nike, and 1300+ + other brands. With hubs in San Francisco, Atlanta, London, and Bangalore, we've served over 125 million consumers worldwide across 10+ billion interactions, 38 countries, and 55 languages.</span></p>
<p><span style="font-weight: 400;">Pioneering the post-purchase movement means navigating into the unknown. Our team thrives on this sense of adventure while nurturing a mindset of innovation. We're a home for big hearts and we leave our egos at the door. We work hard but we always make time to celebrate professional wins, baby showers, birthday parties, and everything in between.</span></p>
<p><em><span style="font-weight: 400;">We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.</span></em></p><div class="content-conclusion"><p><strong><em data-stringify-type="italic">Please read our <a href="https://corp.narvar.com/privacy-policy" target="_blank">Privacy Policy</a></em><em data-stringify-type="italic"> to learn what personal information we collect in connection with your job application, and how we may use and share it. </em></strong></p></div>
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