Data Scientist - ML Engineering at Wizeline

<p><strong>We are:</strong></p> <p>Wizeline, a global AI-native technology solutions provider, develops cutting-edge,&nbsp;<strong>AI-powered</strong>&nbsp;digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of&nbsp;<strong>growth, collaboration,&nbsp;</strong>and&nbsp;<strong>impact.</strong></p> <p>&nbsp;</p> <p><strong>With the right people and the right ideas, there’s no limit to what we can achieve</strong></p> <p><strong>Are you a fit?</strong></p> <p>Sounds awesome, right? Now, let’s make sure you’re a good fit for the role:</p> <p><strong><em>Key Responsibilities</em></strong></p> <ul> <li>Architect end-to-end ML infrastructure across pipelines, serving, monitoring, and governance.</li> <li>Lead deployment of high-impact models (forecasting engines, optimization solvers, NLP models).</li> <li>Design advanced CI/CD workflows using Azure Pipelines, MLflow, and Databricks.</li> <li>Implement model registry, versioning, lineage, and audit compliance.</li> <li>Build monitoring systems for model drift and retraining automation.</li> <li>Mentor MLOps engineers and guide cross-functional platform integration.</li> <li>Drive adoption of MLOps best practices, from containerization to observability.</li> </ul> <p><strong><em>Must-have Skills</em></strong></p> <ul> <li>5–8+ years in ML Engineering, MLOps, or high-scale ML systems.</li> <li>Deep expertise in Spark, Azure Databricks, MLflow, Kubernetes, and Docker.</li> <li>Proven track record deploying ML at enterprise scale with audit and monitoring layers.</li> <li>Familiarity with hybrid/multi-cloud infrastructure.</li> </ul> <p><strong><em>Nice-to-have:</em></strong></p> <ul> <li><strong>AI Tooling Proficiency</strong>: Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows.</li> <li>Leadership experience in ML platform or DevOps teams.</li> <li>Experience with feature stores and feature engineering. AutoML is a plus, H2O is a plus.</li> </ul> <p><strong>What we offer:</strong></p> <ul> <li>A High-Impact Environment</li> <li>Commitment to Professional Development</li> <li>Flexible and Collaborative Culture</li> <li>Global Opportunities</li> <li>Vibrant Community</li> <li>Total Rewards</li> </ul> <p><em>*Specific benefits are determined by the employment type and location.</em></p> <p>&nbsp;</p> <p>Find out more about our culture&nbsp;<a href="https://www.instagram.com/wizelineglobal/" target="_blank">here</a>.</p>