Machine Learning Engineer (AWS)

TL;DR

Machine Learning Engineer (AWS): Implementing AI/ML solutions for demand forecasting and resource optimization in the public transportation industry with an accent on time-series forecasting and feature engineering. Focus on building classical ML models, developing data pipelines on AWS, and creating operational dashboards for capacity modeling.

Location: Remote (Must be based in Colombia)

Company

Tech transformation specialists uniting human expertise with AI to create scalable tech solutions for over 1,000 clients globally.

What you will do

• Conduct EDA and statistical profiling to identify trends and insights from data.
• Develop feature engineering pipelines specifically for time-series forecasting.
• Extract and transform data from relational databases (RDS, Oracle, PostgreSQL) into analytics-ready formats.
• Build and evaluate classical ML models for time-series forecasting and regression using RMSE, MAE, and MAPE metrics.
• Create data visualizations and dashboards using Amazon QuickSight or equivalent BI tools.
• Apply SHAP or other model explainability techniques to interpret model outputs.

Requirements

• 4+ years of experience in data engineering or applied data science roles, preferably with AWS.
• Proficiency in the Python data stack (pandas, NumPy, scikit-learn, matplotlib, seaborn).
• Strong understanding of classical ML modeling, including time-series forecasting and regression.
• Hands-on experience with Amazon SageMaker for model training, evaluation, and Clarify.
• Working knowledge of SQL and dimensional modeling.
• Must be based in Colombia.

Nice to have

• Familiarity with SHAP or other model explainability techniques.
• AWS Certifications: Cloud Practitioner, Data Engineer Associate, or Machine Learning Associate/Specialty.

Culture & Benefits

• Premium healthcare and life insurance.
• Meal vouchers and mobile services subsidy.
• Paid vacations and sick pay.
• Maternity and parental leaves.
• Continuous learning via hirify.global University.