Data Scientist • Senior

Who you are

You have 5–8+ years of experience in ML Engineering, MLOps, or building large-scale ML systems — you've successfully deployed ML solutions at enterprise scale, ensuring audit, governance, and monitoring layers are in place. Your strong expertise with Spark, Azure Databricks, MLflow, Kubernetes, and Docker allows you to design and manage advanced CI/CD workflows effectively.

You are skilled in architecting end-to-end ML infrastructure, including pipelines, model serving, monitoring, and governance — your experience includes building and maintaining monitoring systems to detect model drift and automate retraining cycles. You have a proven track record of leading deployment of high-impact ML solutions such as forecasting engines, optimization models, and NLP use cases.

You thrive in collaborative environments, mentoring MLOps engineers and working closely with platform, data, and product teams to ensure seamless integration of ML solutions. You are passionate about driving the adoption of MLOps best practices across containerization, observability, testing, and scalable infrastructure.

Desirable

Experience with process automation and providing recommendations on effective AI use is a plus — you are always looking for opportunities to streamline workflows and enhance efficiency.

What you'll do

In this role, you will architect and lead the deployment of ML infrastructure that supports various high-impact ML solutions. You will design and manage CI/CD workflows using Azure Pipelines, MLflow, and Databricks, ensuring that all processes are efficient and scalable. Your responsibilities will include implementing model registry, versioning, lineage, and audit-compliant governance frameworks.

You will build and maintain monitoring systems that detect model drift, allowing for timely automation of retraining cycles. As a mentor, you will guide MLOps engineers, fostering a culture of growth and collaboration within the team. You will collaborate with cross-functional teams to ensure that ML solutions are integrated seamlessly into existing platforms and products.

Your role will also involve driving the adoption of MLOps best practices, focusing on containerization, observability, testing, and scalable infrastructure. You will provide insights and recommendations on effective AI use, identifying opportunities to streamline workflows and enhance productivity.

What we offer

Wizeline offers a high-impact environment where you can thrive and grow professionally. We are committed to your development and provide a flexible and collaborative culture that encourages innovation and creativity. You will have access to global opportunities and be part of a vibrant community that values your contributions. Specific benefits are determined by employment type and location, ensuring that you receive the support you need to succeed in your role.