AI/Machine Learning Engineering Specialist

3 semanas atrás

Fortaleza, Brasil beBeeDataEngineer Tempo inteiro

We are seeking a highly skilled Python professional with expertise in data engineering and AI/ML to join our growing team. This role is ideal for someone who loves designing, developing, and maintaining scalable data infrastructure that powers business insights across the organization. The successful candidate will work closely with cross-functional product, engineering, and analytics teams. Key Responsibilities Build, optimize, and maintain ETL/ELT pipelines using Python, modern data engineering frameworks, and Snowflake as a central data warehouse. Architect and manage data workflows, ensuring accuracy, scalability, and reliability. Work closely with data scientists to deploy, monitor, and tune machine learning models. Develop feature engineering pipelines, preprocessing workflows, and model-serving APIs. Integrate data from various sources (APIs, databases, cloud storage, streaming platforms). Implement best practices including versioning, continuous integration/continuous deployment for ML, and automated retraining workflows. Optimize data storage, compute usage, and performance within Snowflake and cloud-native tools. Create and maintain documentation, data catalogs, and operational guides. Monitor system performance and recommend improvements. Required Skills & Experience 3–7+ years of experience as a Data Engineer, Python Engineer, or similar backend/data role. Strong proficiency in Python, including building production-grade data pipelines. Experience with Snowflake—data modeling, tasks, streams, stored procedures, and performance optimization. Experience with AI/ML workflows: feature engineering, inference pipelines, or deploying models. Proficiency in SQL and relational databases. Hands-on experience with at least one cloud platform. Experience using data orchestration tools like Airflow, Prefect, or Dagster. Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or similar. Strong understanding of data modeling, data warehousing, and distributed systems. Preferred Qualifications Experience with Spark, Databricks, or other big-data processing tools. Experience ingesting and transforming data at scale on Snowflake. Familiarity with Kafka, Kinesis, or other streaming platforms. Understanding of CI/CD pipelines. Exposure to deep learning frameworks. Experience working with distributed engineering teams.

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