DevOps Engineer

📋 Description Design and implement supervised and unsupervised ML models for business problems. Lead neural networks (ANN, CNN, Transformer, GAN, RNN) development. Build scalable data pipelines for streaming and batch workloads. Architect lakehouse solutions using Delta/Iceberg architectures. Lead ETL development with Airflow, DBT, Airbyte. Oversee MLOps pipelines for production using SageMaker, Databricks, and Azure ML Studio. 🎯 Requirements Proficient with TensorFlow, PyTorch; CNN, GAN, Transformers. Hands-on with Scikit-learn, Pandas, NumPy. MLOps: SageMaker, Databricks, Azure ML Studio. Spark/Glue/EMR for distributed training. ETL pipelines: Airflow, DBT, Airbyte. Lakehouse: Delta/Iceberg; Great Expectations. Cloud: AWS or Azure; IAM, VPC, Lambda, Kinesis, Kafka. Bachelor's degree required; Master/PhD preferred. 🎁 Benefits Competitive benefits. Collaborative culture.