Design, develop, and test operating systems-level software, compilers, and network distribution software.
Set operational specifications, and formulate and analyze software requirements.
May design embedded systems software.
Developing and maintaining ML pipelines for training, deployment, and monitoring.
Collaborating with data scientists to operationalize models and improve performance.
Implementing CI/CD workflows for ML systems.
Ensuring reproducibility, scalability, and reliability of ML solutions.
Driving automation and optimization across the ML lifecycle.

Bachelor's Degree and 9 years of relevant exempt experience; Master's Degree and 7 years of relevant professional experience; Ph.D. and 4 years of experience.
Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch).
Hands-on experience with ML Ops tools and practices (e.g., MLflow, Kubeflow, Airflow).
Strong understanding of cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
Experience with CI/CD pipelines and version control (Git).
Excellent problem-solving and communication skills.

Senior Machine Learning Engineer

Key skills