[Job - 29381] Senior Machine Learning Engineer, Brazil
Core
Develop, implement, and optimize scalable machine learning models in production to solve complex business problems and transform data into intelligent solutions.
Role type
Senior Machine Learning Engineer (MLOps & Production)
Builds
Production ML models, robust MLOps pipelines, and feature engineering solutions for business clients.
Domain
Technology consulting, Artificial Intelligence, Cloud Computing
Deliverable
production ML models
Required skills
Python, Machine Learning libraries (scikit-learn, TensorFlow, PySpark, XGBoost), GenAI architectures (Amazon Bedrock, RAG, vector databases), API architecture (FastAPI), Apache Airflow, SQL, PostgreSQL, AWS services (SageMaker, S3, EC2, Lambda), Snowflake, DBT, Git
Preferred skills
MLOps platforms (MLflow, Kubeflow), Docker, Kubernetes, Feature Stores (Feast, Tecton), CI/CD for ML, Big Data (Hadoop, Kafka), A/B testing, AWS certifications
Technologies
Python, TensorFlow, PyTorch, XGBoost, Amazon Bedrock, pgvector, OpenSearch, Pinecone, FastAPI, Apache Airflow, PySpark, PostgreSQL, AWS SageMaker, Snowflake, DBT, Git, MLflow, Kubeflow, Docker, Kubernetes, Feast, Tecton, Hadoop, Kafka
Responsibilities
Design and implement scalable ML models for complex business problems; build and maintain robust ML pipelines for deployment and monitoring; create and optimize features using DBT and PySpark; develop and manage data/ML workflows with Apache Airflow; perform distributed data processing; collaborate with data scientists and product teams; monitor model performance and implement improvements; maintain technical documentation.
Seniority
Senior, hands-on IC