Staff ML Scientist

Essential Functions:

• Proficient in exploratory data analysis (EDA) using Python’s scientific libraries including NumPy, Pandas, Matplotlib, Seaborn, and scikit‑learn.
• Strong development experience in Python.
• Hands‑on experience building, training, testing, validating, and productizing machine learning models for high‑performance use cases.
• Solid understanding of core machine learning concepts, including feature engineering, model evaluation, and optimization.
• Experience implementing MLOps best practices, including model versioning, monitoring, and CI/CD pipelines for ML models.
• Hands‑on experience with AWS SageMaker for building, training, tuning, and deploying ML models.
• Hands‑on experience with to AWS services for machine learning workloads, such as S3, EC2, ECR, EKS, Lambda, CloudWatch.
• Strong understanding of model explainability frameworks such as SHAP, and the ability to interpret and explain model behavior.
• Experience debugging and analyzing false positive and false negative cases, including supporting client or production issues.
• Hands‑on experience and solid understanding of deep learning models, with exposure to frameworks such as TensorFlow, PyTorch, or Keras.
• Strong problem‑solving skills with the ability to move beyond tasks and propose improved or alternative solutions.
• Experience with ML lifecycle management and experimentation frameworks such as MLflow

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.