Data Scientist - ML Engineering

Description

Summary: Wizeline is seeking an experienced ML engineer to architect and lead the deployment of high-impact AI-powered digital products and platforms. Highlights: 1. Architect end-to-end ML infrastructure and deploy high-impact models. 2. Mentor MLOps engineers and drive adoption of best practices. 3. Opportunity to work with cutting-edge AI-powered technology solutions. **We are:** Wizeline, a global AI\-native technology solutions provider, develops cutting\-edge, **AI\-powered** 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 **growth, collaboration,** and **impact.** **With the right people and the right ideas, there’s no limit to what we can achieve** **Are you a fit?** Sounds awesome, right? Now, let’s make sure you’re a good fit for the role: ***Key Responsibilities*** * Architect end\-to\-end ML infrastructure across pipelines, serving, monitoring, and governance. * Lead deployment of high\-impact models (forecasting engines, optimization solvers, NLP models). * Design advanced CI/CD workflows using Azure Pipelines, MLflow, and Databricks. * Implement model registry, versioning, lineage, and audit compliance. * Build monitoring systems for model drift and retraining automation. * Mentor MLOps engineers and guide cross\-functional platform integration. * Drive adoption of MLOps best practices, from containerization to observability. ***Must\-have Skills*** * 5–8\+ years in ML Engineering, MLOps, or high\-scale ML systems. * Deep expertise in Spark, Azure Databricks, MLflow, Kubernetes, and Docker. * Proven track record deploying ML at enterprise scale with audit and monitoring layers. * Familiarity with hybrid/multi\-cloud infrastructure. ***Nice\-to\-have:*** * **AI Tooling Proficiency**: 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. * Leadership experience in ML platform or DevOps teams. * Experience with feature stores and feature engineering. AutoML is a plus, H2O is a plus. **What we offer:** * A High\-Impact Environment * Commitment to Professional Development * Flexible and Collaborative Culture * Global Opportunities * Vibrant Community * Total Rewards * *Specific benefits are determined by the employment type and location.* Find out more about our culture here.