Job Description

Responsibilities:

• ML System Development: Design, develop, and maintain scalable and efficient machine learning systems, including writing ML services and APIs.
• Model Deployment: Implement and manage the deployment of machine learning models, including transformer based LLMs, into production environments, ensuring reliability and scalability.
• Infrastructure Management: Collaborate with infrastructure teams to optimize and manage the underlying systems supporting machine learning workflows.
• Data Pipeline Creation: Create robust and efficient data pipelines for collecting, processing, and preparing datasets for machine learning models.
• Collaboration: Work closely with data scientists, researchers, and cross-functional teams to integrate ML solutions into existing software infrastructure.
• Performance Optimization: Continuously optimize and improve the performance of machine learning algorithms and systems.
• Documentation: Develop and maintain documentation for machine learning systems, APIs, and data pipelines to ensure clarity and ease of use for team members.

Our ideal candidates would:

• 3+ years of experience including working on designing multi-component systems
• Strong grasp of one high-level language like Python.
• General awareness of SQL and database design concepts
• Solid understanding of testing fundamentals
• Strong communication skills
• should have prior experience in managing and executing technology products.
• Decent understanding of various Gen AI based ML approaches
• Experience in building agentic architectures using langgraph or similar libraries

Bonus:

• Prior experience working with high-volume, always-available web-applications
• Experience working with cloud
• Knowledge of cloud platforms such as AWS, GCP, or Azure.
• Experience with deploying small and big open source LLMs in production environments using containerization tools like Docker
• Experience in Distributed systems.
• Experience working with Start-up is a plus point.