Senior ML Engineer

Sonatafy Technology - Mexico

Senior ML Engineer analyzing large datasets and building machine learning models for Sonatafy Technology. Collaborating with stakeholders in a fast-paced, client-first culture.

Posted 6/20/2026full-timeRemote • 🇲🇽 MexicoSeniorWebsite

Tech Stack

Tools & technologies

NumpyPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Analyze large datasets to surface trends, patterns, and actionable business insights.
Build and maintain data models, transformations, and pipelines using SQL and dbt.
Collaborate with stakeholders to define metrics, KPIs, and reporting requirements.
Support data governance, ensuring data quality, integrity, and accessibility across the organization.
Document processes, workflows, and analysis outcomes for cross-functional teams.
Design, build, and evaluate supervised and unsupervised ML models (classification, regression, clustering, forecasting).
Lead problem framing conversations with stakeholders to translate business questions into ML-ready problem statements.
Conduct feature engineering, selection, and transformation to prepare data for model training.
Validate and communicate model performance using appropriate evaluation metrics (AUC, RMSE, F1, precision/recall, etc.).
Support lightweight model deployment and monitoring, flagging performance drift and recommending retraining triggers.
Contribute to experiment design and A/B testing frameworks where applicable.

Requirements

What you’ll need

5+ years of experience in Data Analytics, Data Science, or a combined analytics and ML role.
Demonstrated experience building and deploying ML models in a business context, not just academic or exploratory work.
Strong analytical and problem-solving mindset with the ability to translate complex data into clear, actionable insight.
Excellent communication skills to work effectively with both technical and non-technical stakeholders.
Python proficiency for both data wrangling and ML model development: Data libraries: pandas, NumPy, matplotlib, seaborn ML libraries: scikit-learn, XGBoost, LightGBM, or equivalent.
Strong SQL skills including querying, optimization, and data modeling.
Experience with dbt for building and version-controlling data transformations.
Solid understanding of relational databases and data warehouse concepts.
Comfort with statistical reasoning: distributions, hypothesis testing, regression, and uncertainty quantification.

Benefits

Comp & perks

competitive compensation
remote-first lifestyle
career growth opportunities across industries and technologies

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data analysisdata modelingSQLdbtmachine learningfeature engineeringmodel evaluationA/B testingPythonstatistical reasoning

Soft Skills

analytical mindsetproblem-solvingcommunicationcollaborationdocumentation