Jobs → Customer Support → ML Architect

About the Role We are looking for an experienced ML Architect with strong hands-on expertise in AWS, Databricks, and MLOps to design and deliver scalable, secure, production-ready machine learning solutions. Key Responsibilities • Define ML architecture and platform strategy across AWS and Databricks • Assess existing Databricks implementations and recommend improvements • Design end-to-end ML workflows, including feature engineering, training, validation, deployment, and monitoring • Implement MLOps practices using Databricks and MLflow • Build batch and real-time model inference solutions • Leverage Unity Catalog, Feature Engineering, Model Serving, Delta Lake, Lakehouse Monitoring, and Databricks Workflows • Integrate Databricks with AWS services, including S3, IAM, KMS, SageMaker, Lambda, and CloudWatch • Establish architecture standards, security controls, governance, and cost-optimization practices • Collaborate with data scientists, data engineers, platform teams, and business stakeholders • Provide technical leadership, documentation, and knowledge transfer Requirements • Extensive experience in enterprise ML architecture and production ML platforms • Strong hands-on experience with Databricks Lakehouse architecture • Expertise in MLflow, model lifecycle management, and MLOps • Strong AWS architecture and implementation experience • Experience with CI/CD, infrastructure as code, automated testing, and model monitoring • Proficiency in Python, SQL, Apache Spark, and PySpark • Experience with batch and real-time inference, feature engineering, model drift detection, and retraining • Strong understanding of cloud security, IAM, encryption, data governance, and responsible AI