✦ Luna Orbit — AI & Machine Learning

Senior Data Scientist (AI Deployment)

at Braze

📍 São Paulo Onsite Posted March 19, 2026
Type Full-Time
Experience senior
Exp. Years 3-5+ years
Education Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or related field
Category AI & Machine Learning

This role involves developing and deploying AI and machine learning models, collaborating with customer teams, and advancing product AI capabilities.

  • Collaborate on AI deployments
  • Improve reinforcement learning algorithms
  • Develop reusable data pipelines
  • Contribute to product AI strategy
  • Support customer success with AI solutions

The position requires expertise in Python, TensorFlow, Keras, scikit-learn, reinforcement learning, data pipelines, and cloud deployment using GCP and Kubernetes.

The ideal candidate is a senior data scientist or machine learning engineer with 3+ years of experience working with large-scale data, proficient in Python and ML libraries, and experienced in deploying models in production environments.

3-5+ years experience as Data Scientist or ML Engineerproficiency in Python and ML librariesexperience with large-scale datamodel deploymentdata pipeline developmentcustomer-facing experience
DevOps toolsKubernetesTerraformGCPAirflowdata integration
PythonTensorFlowKerasscikit-learnCatBoostXGBoostSQLGCPKubernetesTerraformAirflow
pythontensorflowkerasscikit-learnreinforcement learningdata pipelinesmodel deploymentlarge-scale data
PythonPandasTensorFlowKerasscikit-learnCatBoostXGBoostSQLML pipelinesmodel deploymentreinforcement learningAPI developmentdata integration
collaborationproblem-solvingtechnical expertisecommunicationadaptabilityteamwork
Industry SaaS
Job Function AI model development and deployment in a SaaS environment
Role Subtype AI Deployment Engineer
Tech Domains Python, TensorFlow, Keras, scikit-learn, Google Cloud Platform, Kubernetes, Terraform, Airflow
data scientistmachine learning engineerpythontensorflowkerasscikit-learncatboostxgboostsqlml pipelinesmodel deploymentreinforcement learningapi developmentdata integrationgcpkubernetesterraformairflowlarge-scale datacustomer-facing

Less than 3 years experience in data science or ML engineering, Lack of proficiency in Python and ML libraries, No experience with large-scale data or model deployment, Unwilling to work onsite in São Paulo

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