Data Scientist- ML Engineering

AI overview

Architect end-to-end ML infrastructure and lead deployments of high-impact ML solutions, while mentoring engineers and driving adoption of MLOps best practices.

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, 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:

  • 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.

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