Data Scientist - ML Engineering

Wizeline

Colombia based Remote (Colombia) Remote permanent

Posted: February 23, 2026

Quick Summary

We are looking for a Data Scientist - ML Engineering to join our team, working remotely and contributing to the development of AI-powered digital products. The ideal candidate should have a strong background in computer science and machine learning, and be familiar with Python, TensorFlow, and scikit-learn. The successful candidate will be expected to work on complex data analysis and model development projects.

Required Skills

Job Description

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:

Requirements

• Bachelor's required; Master's preferred in CS, Engineering, or related.

• 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.

Soft Skills

1. Strategic, persuasive, and business-oriented communication.

• Strong storytelling to explain, defend, and "sell" complex solutions.

• Ability to lead complex conversations with clients and senior stakeholders.

• Clear, structured, and confident responses to objections or ambiguous scenarios.

• Ability to translate technical topics into business impact and decision-making.

• Ability to build trust, credibility, and alignment through communication.

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.

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