IconRappi

Are you ready to build the future of Latin America? 🚀

At Rappi, we build the SuperApp that changes the lives of millions of people every day. We are a team driven by speed, execution, and real results.

This is where things happen. If you are excited by solving real-scale problems, learning at record speed, and seeing the impact of your ideas in a matter of days, this is your place.

Want to build the systems that move millions of people every day? 🛠️

The challenge

As a Senior Machine Learning Engineer at Rappi, you will lead the design, development, and implementation of high-impact Machine Learning solutions for our SuperApp, with a focus on pricing. This includes models for setting prices, fees, discounts, and promotions based on demand, elasticity, user behavior, and market context, while balancing growth, profitability, and user experience. You will work with Machine Learning Engineers, Data Scientists, Software Engineers, Product Managers, and business stakeholders to turn complex problems into scalable, data-driven solutions. You will own the entire model lifecycle: framing the problem, preparing the data, performing feature engineering and experimentation, and then evaluating, deploying, monitoring, and continuously improving models in production. We are looking for someone with strong technical depth and business acumen who can define the technical direction of their initiatives, raise the bar for the team, and support the growth of more junior team members.

Your challenges

Frame pricing and promotion problems together with Product and Business teams, and translate them into Machine Learning solutions with clear success metrics.
Design and build robust features, datasets, and data pipelines (for example, demand signals, price sensitivity, and purchasing behavior).
Develop, evaluate, and compare models, and define the most suitable modeling strategy for each problem.
Design and lead experiments, such as A/B tests for prices or discounts, to measure their causal impact on conversion, orders, revenue, and margin.
Deploy models to production as scalable and reliable services, in collaboration with Software Engineers.
Define and implement model monitoring, detect degradation, and lead incident investigations in production.
Conduct code reviews, define best practices, and raise the team’s technical standards.
Mentor other team members and share learnings.
Contribute to the pricing technical roadmap and propose new opportunities for impact.
Stay up to date with new Machine Learning techniques, tools, and best practices.

You will be a great fit

Experience: 5 or more years in Machine Learning Engineering or Data Science roles, with models deployed to production.
Education: Completed university degree (postgraduate studies in quantitative fields preferred)
English: Upper-intermediate
Experience with pricing, promotions, revenue management, or demand modeling projects (highly preferred)
Previous experience at tech startups, e-commerce companies, or marketplaces (preferred)
Experience leading technical initiatives or mentoring others (preferred)
Experience working in agile squads and remote-first environments (preferred)

Tech profile

What you need to master

Proficiency in Python and SQL
Git and collaborative development best practices (code reviews, CI/CD)
Pandas / NumPy
Scikit-learn, XGBoost / LightGBM
TensorFlow / PyTorch
Docker
Experience with AWS / GCP / Azure
Strong experience across the entire model lifecycle: training, validation, deployment, monitoring, and retraining.
Experience in MLOps: training pipelines, orchestration (Airflow or similar), feature stores, model versioning, and drift detection.
Design and implementation of APIs and services to serve models in production, with attention to latency, scalability, and reliability.
Advanced statistics and experimentation (A/B test design, causal inference, statistical power analysis).
Experience in pricing: demand elasticity, forecasting, dynamic pricing, optimization models, or uplift and causal models.
Strong fundamentals in algorithms, data structures, and system design.

What makes you different

Analytical thinking and the ability to solve ambiguous and complex problems.
Sound judgment in making technical decisions and explaining the trade-offs between accuracy, complexity, cost, and business impact.
End-to-end ownership of the initiatives under their responsibility.
Clear communication with technical and business audiences, including the ability to influence stakeholders.
Mentoring and supporting junior and semi-senior professionals.
Ability to give and receive feedback.
Autonomy to prioritize and take initiatives from idea to production.
Focus on results and measurable impact.
Curiosity and continuous learning.
Proactivity in identifying opportunities and proposing new initiatives.
Business acumen to balance growth, profitability, and user experience.

We believe our talent deserves the best tools to make an impact with purpose.

Colombia 🇨🇴

At Rappi, diversity makes us stronger

We believe diverse and inclusive teams build the best products, and we actively seek people of all genders, ages, backgrounds, religions, and sexual orientations. If you want to build the future of Latin America, your place is here.

Will you join the team? At Rappi, the limit is the one you set for yourself. If you are excited about learning in motion and building solutions that scale to millions, we want to meet you.

The challenge

Your challenges

Frame pricing and promotion problems together with Product and Business teams, and translate them into Machine Learning solutions with clear success metrics.

Design and build robust features, datasets, and data pipelines (for example, demand signals, price sensitivity, and purchasing behavior).

Develop, evaluate, and compare models, and define the most suitable modeling strategy for each problem.

Design and lead experiments, such as A/B tests for prices or discounts, to measure their causal impact on conversion, orders, revenue, and margin.

Deploy models to production as scalable and reliable services, in collaboration with Software Engineers.

Define and implement model monitoring, detect degradation, and lead incident investigations in production.

Conduct code reviews, define best practices, and raise the team’s technical standards.

Mentor other team members and share learnings.

Contribute to the pricing technical roadmap and propose new opportunities for impact.

Stay up to date with new Machine Learning techniques, tools, and best practices.

You will be a great fit

Experience: 5 or more years in Machine Learning Engineering or Data Science roles, with models deployed to production.

Education: Completed university degree (postgraduate studies in quantitative fields preferred)

English: Upper-intermediate

Experience with pricing, promotions, revenue management, or demand modeling projects (highly preferred)

Previous experience at tech startups, e-commerce companies, or marketplaces (preferred)

Experience leading technical initiatives or mentoring others (preferred)

Experience working in agile squads and remote-first environments (preferred)

Tech profile

What you need to master

Proficiency in Python and SQL
Git and collaborative development best practices (code reviews, CI/CD)
Pandas / NumPy
Scikit-learn, XGBoost / LightGBM
TensorFlow / PyTorch
Docker
Experience with AWS / GCP / Azure
Strong experience across the entire model lifecycle: training, validation, deployment, monitoring, and retraining.
Experience in MLOps: training pipelines, orchestration (Airflow or similar), feature stores, model versioning, and drift detection.
Design and implementation of APIs and services to serve models in production, with attention to latency, scalability, and reliability.
Advanced statistics and experimentation (A/B test design, causal inference, statistical power analysis).
Experience in pricing: demand elasticity, forecasting, dynamic pricing, optimization models, or uplift and causal models.
Strong fundamentals in algorithms, data structures, and system design.

What makes you different

Analytical thinking and the ability to solve ambiguous and complex problems.
Sound judgment in making technical decisions and explaining the trade-offs between accuracy, complexity, cost, and business impact.
End-to-end ownership of the initiatives under their responsibility.
Clear communication with technical and business audiences, including the ability to influence stakeholders.
Mentoring and supporting junior and semi-senior professionals.
Ability to give and receive feedback.
Autonomy to prioritize and take initiatives from idea to production.
Focus on results and measurable impact.
Curiosity and continuous learning.
Proactivity in identifying opportunities and proposing new initiatives.
Business acumen to balance growth, profitability, and user experience.