BS/MS in Computer Science, Data Science, or a related field, or equivalent work experience 6-10 years of experience as an ML Engineer Experience establishing and driving best practices for ML/MLOps Strong understanding of core ML concepts Hands-on experience with modern ML frameworks (CatBoost, LightGBM, TensorFlow, or PyTorch) Experience with large-scale data processing and transformation pipelines Experience deploying models to cloud platforms (AWS, GCP, or Azure) Experience leveraging containerization and orchestration technologies (Docker and Kubernetes) Experience with CI/CD pipelines and MLOps tooling (e.g., MLflow, Feast, Weights & Biases) Ability to thrive in ambiguous environments with minimal guidance Proficient in English