ML Engineer

Qualifications

Requirements

• At least 3-5 years of experience as an ML Engineer, MLOps Engineer, or equivalent.
• Strong proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Proven experience with AWS ML services, including SageMaker, Glue, Lambda, Step Functions, S3, and CloudWatch.
• Familiarity with CI/CD and test automation tools (e.g., PyTest, Unittest, GitHub Actions, CodePipeline).
• Experience with infrastructure-as-code, versioning, and model registries.
• Solid understanding of MLOps practices, testing strategies, and production ML requirements.
• Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering, or related field.