Overview We are seeking a highly skilled and experienced Machine Learning Engineer to join the Merchants and Makers Data Science Models Team. In this role, you will build and optimize models that directly impact merchant profitability and Ads performance, such as the Profit Model and Smart Bidding systems. You will have the opportunity to make a significant impact on business performance and growth within a cutting-edge tech environment. We are committed to equal opportunity and provide opportunities regardless of gender identity, race, religion, nationality, age, disability, training or experience. Responsibilities Design, implement, and deploy core machine learning models such as the Profit Model (for optimal promo configuration) and Smart Bidding (for Ads optimization). Collaborate with a cross-functional team of engineers, data scientists, and product managers to develop, test, and deploy machine learning models for merchant-facing platforms. Perform feature engineering and selection to improve the overall effectiveness of merchant data science models. Work closely with the data infrastructure team to ensure seamless integration of machine learning models with existing systems and data pipelines. Continuously monitor and analyze merchant model performance (e.g., ROAS, profit uplift), identifying opportunities for improvement and implementing changes. Leverage and evaluate AI tools to accelerate model development and improve code quality and efficiency. Mentor junior team members and contribute to the growth of the team\'s expertise in machine learning and merchant science. Qualifications BSc or MSc in Computer Science, Engineering, or a related field with a focus on machine learning; PhD is a plus. 4+ years of experience in machine learning engineering/data science, preferably in Merchants Ads optimization (e.g., Smart Bidding, ROAS optimization) or Pricing/Promotions models (e.g., Profit Model) with demonstrable customer and business results. Strong proficiency in Python, with experience in ML libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn. Familiarity with data processing and ETL tools such as Airflow, Snowflake, Postgres, Kafka, and Redis. Proven experience with large-scale, complex systems and the ability to adapt to a fast-paced, rapidly evolving environment. Excellent problem-solving and analytical skills, with a passion for optimizing algorithms and models for high performance. Strong communication and collaboration skills, with the ability to work effectively within a diverse, cross-functional team. Fluency in Spanish (written and spoken) is required; proficiency in English is strongly preferred. Preference will be given to candidates in Latin America. Globally located candidates are possible in the right circumstances. Employer Rappi Technology Argentina #J-18808-Ljbffr