Artificial Intelligence Engineer

About the Role Join a fast-paced engineering company that serves as a leading platform for researchers worldwide. As a Senior Agentic AI Engineer in our vibrant Bangalore team, you will tackle significant technical challenges while contributing to groundbreaking solutions that impact millions. This role offers a unique opportunity for professional growth within a dynamic startup environment, driven by innovation and a commitment to excellence. Responsibilities

• Design, develop, and maintain scalable machine learning systems by writing efficient ML services and APIs.
• Implement and manage the deployment of machine learning models, ensuring reliable performance in production environments.
• Collaborate with infrastructure teams to optimize the underlying systems that support machine learning workflows.
• Create robust data pipelines to collect, process, and prepare datasets for machine learning applications.
• Work closely with cross-functional teams, including data scientists and researchers, to integrate ML solutions effectively.
• Continuously optimize machine learning algorithms to enhance performance and system efficiency.
• Develop and maintain documentation for ML systems to facilitate understanding among team members. Requirements
• Minimum of 3 years of experience in designing and implementing multi-component systems.
• Strong proficiency in a high-level programming language, particularly Python.
• General understanding of SQL and foundational concepts of database design.
• Solid grasp of testing fundamentals to ensure reliable system functionality.
• Excellent communication skills to collaborate effectively with cross-functional teams.
• Prior experience in managing and executing technology products with successful outcomes.
• Decent knowledge of various Generative AI-based machine learning approaches.
• Experience in building agentic architectures utilizing libraries such as langgraph or comparable tools. Nice to Have
• Experience working on high-volume, always-available web applications.
• Familiarity with cloud computing environments and services.
• Knowledge of cloud platforms like AWS, GCP, or Azure.
• Experience deploying both small and large open-source LLMs in production using containerization tools like Docker.
• Background in distributed systems and related architectures.
• Experience in a startup environment is an advantage.