Description

Build and maintain production-grade machine learning systems, focusing on model deployment, optimization, and lifecycle management.

This role is on-site.

Responsibilities

• Build APIs and services to serve ML models in production environments.
• Optimize model inference speed and scalability to meet performance targets.
• Develop automated pipelines for training and deployment workflows.
• Embed ML services into existing production applications and microservices.
• Monitor model performance and reliability, addressing issues in real-time.

Required Skills

• 7-10 years of software engineering experience with a focus on machine learning systems.
• Strong software engineering background with proficiency in Python.
• Experience designing and implementing REST APIs and microservices architectures.
• Hands-on experience with Docker and Kubernetes for containerization and orchestration.
• Familiarity with major cloud platforms for deploying ML workloads.
• Deep understanding of the machine learning lifecycle and common deployment challenges.

Preferred Skills

• Experience with large-scale distributed systems and high-throughput data processing.
• Contributions to open-source ML infrastructure or tools.

Key Skills

Education

Any Gradute