[Hiring] Staff Machine Learning Engineer @Grupo QuintoAndar

Role Description

At QuintoAndar we use Machine Learning (ML) to build delightful experiences and solve complex problems. We are at a maturity level where scaling those ML systems is also a challenge. We need Machine Learning Engineers to bring great models to production as effective ML-based products and features, and also evolve this ecosystem.

You can learn more about our ML pipeline and platform here and here . Or play a bit with Butterfree here and discover how features are transformed to our Feature Store.

Machine Learning Engineer Responsibilities at QuintoAndar

• Combine Software Engineering and Data Science disciplines to create production-ready Machine Learning models;
• Integrate other engineering services and systems with our ML services;
• Develop frameworks and platform to build, deploy, serve and monitor ML-based services;
• Collaborate with Software Engineers, Data Engineers and Data Scientists along the way of the modeling pipeline:
• Features preparation
• Model training
• API development
• Service deployment
• Predictions and features monitoring
• Model retraining
• Assure health and quality of ML services;
• Foster best practices for infrastructure and coding regarding machine learning specific requirements;
• Contribute to vision and architecture to scale ML solutions at QuintoAndar's business;
• Participate of problem contextualization, solution scope, product discovery, design and implementation of ML-based products and/or ML Platform;
• Manage technical debt regarding a strategic trade-off between delivering value in the short term and expanding ML capabilities in the long term;
• Bridge professionals and technical dependencies between non-ML services and ML services.

Qualifications

• Strong software engineering and python skills;
• Solid background in Machine Learning;
• Proven experience in productionizing ML models, with deep expertise in deploying and maintaining ML services;
• Good cloud-based infrastructure skills;
• Experience with MLOps tools and libraries (Ex: MLflow, Kubeflow, AWS SageMaker, Google AI Platform, etc);
• Experience developing RESTful APIs;
• Experience with tough technical challenges;
• Humility, curiosity and avid interest in learning;
• Ability to deal with changes in a fast-paced environment;
• Good communication and teamwork skills;
• Orientation to business value.

Requirements

• MSc. or PhD in Computer Science, Engineering, Statistics, or other relevant technical fields;
• Experience with Deep Learning models;
• Experience with LLMs, AI Agents and chatbots;
• Experience with Spark;
• Experience in fast-growing start-ups or in high-tech companies.

Benefits

• Competitive salary;
• Profit sharing;
• Meal allowance;
• Health insurance;
• Dental plan;
• Life insurance;
• Childcare subsidy and Atypical Parenthood subsidy;
• Wellhub;
• Employee assistance program (mental health, social, legal, and financial support);
• Extended parental leave;
• Day off on birthday, Mother’s Day, and Father’s Day;
• Benefits Club (discounts on everyday services);
• Discounts at educational institutions;
• Reading kit for children – PlayKids.