onsite
Machine Learning Engineer - Netskope
ML Engineer
Develop and deploy advanced machine learning models for cloud security solutions, leveraging Python, deep‑learning frameworks, and cloud infrastructure to protect data across distributed environments.
About the role
Key Responsibilities
- Design, implement, and optimize machine learning algorithms for threat detection, data classification, and anomaly detection in a cloud security platform.
- Collaborate with product, security, and infrastructure teams to integrate ML models into production services at scale.
- Build and maintain data pipelines for large‑scale telemetry ingestion, feature engineering, and model training using cloud services.
- Deploy, monitor, and continuously improve models in containerized environments (Docker, Kubernetes) on AWS.
- Conduct experiments, evaluate model performance, and publish findings to drive product innovation.
Requirements
- Strong proficiency in Python and experience with deep‑learning libraries such as TensorFlow or PyTorch.
- Hands‑on experience building and deploying ML models in cloud environments, preferably AWS.
- Solid understanding of data engineering concepts, including ETL pipelines, feature stores, and large‑scale data processing.
- Familiarity with containerization (Docker) and orchestration (Kubernetes) for scalable model serving.
- Background in security, networking, or related domains is a plus.
Skills
pythontensorflowpytorchawsdockerkubernetesmachine learning