Senior Machine Learning Engineer

Bachelor’s degree in a quantitative discipline, such as Computer Science, Data Science, Mathematics, or Statistics preferred.
2-3+ years of relevant experience in developing code in programming languages such as Python or Java.
Experience with data preprocessing, feature engineering, and model evaluation techniques.
Experience with containerization technologies such as Docker and Kubernetes.
Familiarity with cloud computing platforms such as AWS, GCP, or Azure.
Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
Experience with SQL for data extraction.
Ability to work independently and collaboratively in a fast-paced, agile environment.

Develop and deploy ML pipelines to solve specific business problems.
Deploy ML models into production systems, ensuring scalability, reliability, and efficiency.
Collaborate with data scientists and domain experts to identify and engineer relevant features for improving model accuracy and robustness.
Work closely with product managers, software engineers, and other stakeholders to understand requirements, prioritize tasks, and deliver ML solutions that meet business objectives.
Implement monitoring and logging mechanisms to track model performance in real-time and address any issues that arise.
Conduct hyper parameter optimization to fine-tune model performance and improve generalization on unseen data.
Design, prototype and build ML systems, frameworks, pipelines, libraries, utilities and tools that process massive data for ML tasks.
Translate data science prototypes into scalable production implementations.
Partner with data scientists to troubleshoot and optimize complex data pipelines.