Machine Learning Engineer

Overview: • This role is crucial for supporting the migration of AI and ML models from the analytics phase to a full-scale IT environment. The successful candidate will work closely with data science partners to productionize pricing models, ensuring they are scalable, secure, and integrated with IT systems. This involves building data engineering pipelines and utilizing a tech stack including Airflow, Vertex AI, and Kubernetes. The position requires a strong foundation in SQL and Python, with a collaborative mindset to work across functions. Job Must Haves: • 5-6 YOE with ML/Data Engineering • Experience with SQL and Python • Knowledge of CI/CD integrations (pipelines, automation, deployments) • Experience with Airflow, Vertex AI, Dataform, GitHub Actions, Terraform, and Kubernetes Job Nice to Haves: • GCP background • Experience with MLflow, Kubeflow, or SageMaker What the responsibilities are of the right candidate: • Supporting the migration and productionization of AI and ML models. • Building and maintaining data engineering pipelines. • Collaborating with cross-functional teams to ensure model scalability and security. • Participating in live coding interviews and technical discussions.