Machine Learning Engineer

A highly successful, fully bootstrapped technology firm and a leader in the AI-Performance Marketing sector.

Since its inception, the company has remained consistently profitable and independent of external VC funding, fueled by a robust and growing global client base.

The organization develops sophisticated AI-driven systems that generate high-intent leads, enabling businesses to scale rapidly while optimizing operational efficiency.

Located in the Central District (prime location near the train), the company maintains a high-intensity, boutique environment of approximately 30 experts, fostering a culture of rapid execution and technical excellence.

The Role & Responsibilities

• As a foundational member of a newly formed ML Research team, you will take full end-to-end ownership of Machine Learning projects, bridging the gap between applied research and large-scale production:
• Full-Cycle Ownership: Leading the entire ML lifecycle from problem formulation and data exploration to feature engineering, model development, and production monitoring.
• Predictive Modeling: Extracting high-value predictive signals from complex, unstructured Tabular Data to drive real-time marketing decisions.
• Production-Grade ML: Collaborating with Data Engineering to deploy models into high-scale environments, with a focus on optimizing for Inference Latency and throughput.
• Rigorous Methodology: Maintaining elite standards in experimental design, causality, and model validation using modern MLOps frameworks (Experiment Tracking, Model Versioning, etc.).
• Strategic Impact: Formulating the AI roadmap that directly influences the company’s core business engine and its ability to scale in a competitive global market.
• The Stack- Tabular ML, Applied Research, Big Data, MLOps, Cloud ML, Deployment Pipelines, and Production Monitoring.

Requirements

• Professional Depth: At least 5 years of experience as an ML Researcher or Data Scientist within high-caliber product environments – Mandatory.
• AI/ML Mastery: Proven track record in developing and deploying complex Machine Learning models that solve real-world business problems – Mandatory.
• Tabular Expert: Significant experience working with large-scale Tabular Data and extracting insights from noisy, non-standardized datasets.
• Engineering Mindset: Strong hands-on capabilities in Python and a deep understanding of what it takes to bring research into a Production environment.
• Scientific Rigor: A deep understanding of statistical modeling, evaluation metrics, and experimental design.

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