MLOps Manager

Summary

Join QuintoAndar's growing team as an MLOps Manager and lead the efforts in streamlining the development, deployment, and monitoring of our machine learning systems. You will oversee a cross-functional team, collaborate with Data Science Leaders, optimize model deployment and monitoring, and foster best practices. This role requires a general understanding of machine learning concepts, solid software and data engineering skills, experience with cloud services, and proficiency in Python. QuintoAndar offers a competitive salary package, various benefits, and a fast-paced, dynamic environment with ample opportunities for career growth and collaboration. The company is committed to diversity and inclusion and provides a remote-first work model.

Requirements

• Possess a general understanding of machine learning concepts: regression and classification, clustering, neural networks, feature selection, cross-validation, curse of dimensionality, bias-variance tradeoff, model explainability, etc
• Demonstrate a good understanding of the engineering challenges of deploying machine learning systems to production
• Possess a solid understanding of software and data engineering best practices
• Have experience with cloud-based services
• Be proficient in Python or another major programming language
• Be up-to-date with recent advances in Machine Learning Engineering, and willing to share his/her knowledge with the other members of the Data Science Chapter
• Possess excellent written and verbal technical communication skills
• Be product-minded and help guide QuintoAndar's Machine Learning Platform long-term roadmap
• Have experience leading teams and managing careers

Responsibilities

• Lead the MLOps Squad: Oversee a cross-functional team of Machine Learning Engineers and Data Scientists focused on building and maintaining our ML Platform. You'll guide the team in balancing long-term vision with the delivery of high-impact features
• Collaborate with Data Science Leaders: Work closely with the Data Science team to deeply understand and deliver on ML platform requirements, ensuring seamless integration between models and production systems
• Optimize Model Deployment & Monitoring: Ensure the smooth deployment and ongoing performance of models, implementing best practices for monitoring, scaling, and addressing model drift
• Foster Best Practices: Lead by example in promoting infrastructure and coding standards that align with machine learning requirements, ensuring efficient, scalable systems
• Drive Automation & Efficiency: Automate workflows, integrate new tools, and streamline pipelines to support fast iteration, model updates, and continuous delivery

Preferred Qualifications

• Have previously worked on building machine learning platforms
• Have experience with MLOps tools and libraries (Ex: Kubeflow, MLflow, AWS SageMaker, Google AI Platform, etc)
• Have a MSc. (or Undergrad + intense experience) in Computer Science, Engineering, Statistics, Economics or other relevant technical field
• Have experience working at fast-growing startups
• Be up-to-date with cloud solutions (preferably AWS)

Benefits

• Competitive salary package
• Bonus
• Meal allowance ("Flash Benefícios")
• Public transportation allowance*
• Health plan
• Dental plan (optional)
• Life insurance
• Daycare subsidy
• Subsidy to sports practicing (Wellhub)
• Extended maternity and paternity leave
• Reserved room for breast-feeding
• Discount on our parking lot
• Language learning support
• Free transfer from Vila Madalena and Fradique Coutinho stations to the office
• Free bike rack in our parking lot