Data Scientist- ML Engineering
hace 2 semanas
Get AI-powered advice on this job and more exclusive features. Direct message the job poster from Wizeline 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 Sounds awesome, right? Now, let’s make sure you’re a good fit for the role: Key Responsibilities Architect end-to-end ML infrastructure, including pipelines, model serving, monitoring, and governance. Lead deployment of high-impact ML solutions such as forecasting engines, optimization models, and NLP use cases. Design and manage advanced CI/CD workflows using Azure Pipelines, MLflow, and Databricks. Implement model registry, versioning, lineage, and audit-compliant governance frameworks. Build and maintain monitoring systems to detect model drift and automate retraining cycles. Mentor MLOps engineers and collaborate with platform, data, and product teams to ensure seamless integration. Drive adoption of MLOps best practices across containerization, observability, testing, and scalable infrastructure. Must‑have Skills 5–8+ years of experience in ML Engineering, MLOps, or building large-scale ML systems. Strong expertise with Spark, Azure Databricks, MLflow, Kubernetes, and Docker. Proven track record deploying ML solutions at enterprise scale with audit, governance, and monitoring layers. Experience designing ML infrastructure and CI/CD pipelines in cloud environments. Knowledge of hybrid or multi‑cloud architectures. Bachelor’s degree required; Master’s preferred in Computer Science, Engineering, or related fields. 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. What we offer Commitment to Professional Development Flexible and Collaborative Culture Total Rewards *Specific benefits are determined by the employment type and location. Find out more about our culture here. #J-18808-Ljbffr
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